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Review Article
Published: 27 June 2019

The human stress response

Georgina Russell 1 &
Stafford Lightman ORCID: orcid.org/0000-0002-8546-9646 1

Nature Reviews Endocrinology volume 15 , pages 525–534 ( 2019 ) Cite this article

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Adrenal cortex hormones
Circadian rhythms
Multihormonal system disorders
Stress signalling

The human stress response has evolved to maintain homeostasis under conditions of real or perceived stress. This objective is achieved through autoregulatory neural and hormonal systems in close association with central and peripheral clocks. The hypothalamic–pituitary–adrenal axis is a key regulatory pathway in the maintenance of these homeostatic processes. The end product of this pathway — cortisol — is secreted in a pulsatile pattern, with changes in pulse amplitude creating a circadian pattern. During acute stress, cortisol levels rise and pulsatility is maintained. Although the initial rise in cortisol follows a large surge in adrenocorticotropic hormone levels, if long-term inflammatory stress occurs, adrenocorticotropic hormone levels return to near basal levels while cortisol levels remain raised as a result of increased adrenal sensitivity. In chronic stress, hypothalamic activation of the pituitary changes from corticotropin-releasing hormone-dominant to arginine vasopressin-dominant, and cortisol levels remain raised due at least in part to decreased cortisol metabolism. Acute elevations in cortisol levels are beneficial to promoting survival of the fittest as part of the fight-or-flight response. However, chronic exposure to stress results in reversal of the beneficial effects, with long-term cortisol exposure becoming maladaptive, which can lead to a broad range of problems including the metabolic syndrome, obesity, cancer, mental health disorders, cardiovascular disease and increased susceptibility to infections. Neuroimmunoendocrine modulation in disease states and glucocorticoid-based therapeutics are also discussed.

The hypothalamic–pituitary–adrenal (HPA) axis is a key system that synchronizes the stress response with circadian regulatory processes.

Regulation of the HPA axis is very dynamic with both ultradian and circadian oscillations.

Short-term and longer-term stress result in different regulatory mechanisms involving hypothalamic, pituitary and adrenal activity, as well as cortisol metabolism.

Chronic elevation and nonphysiological patterns of cortisol result in poor cognitive, metabolic and immune function.

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Cues that entrain or synchronize the body’s 24-h cycle

Biological rhythms that occur with a frequency of <24 h.

A biochemical oscillator with phases synchronized with solar time.

Neural pathways involving at least one relay.

The microcirculation that allows transport of hypothalamic hormones to the pituitary gland.

The threshold power of (solar) electromagnetic radiation needed to exert an effect.

Repetitive body movements that serve no biological function.

Behaviours engaged for a specific functional purpose.

Any biological process that displays an oscillation of approximately 24 h.

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Russell, G., Lightman, S. The human stress response. Nat Rev Endocrinol 15 , 525–534 (2019). https://doi.org/10.1038/s41574-019-0228-0

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DOI : https://doi.org/10.1038/s41574-019-0228-0

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Article Contents

What is stress, what is the stress response, how does chronic stress affect your health, how do you know you’re stressed out, what should you do with this information, stress and your health.

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Bruce McEwen, Robert Sapolsky, Stress and Your Health, The Journal of Clinical Endocrinology & Metabolism , Volume 91, Issue 2, 1 February 2006, Page E2, https://doi.org/10.1210/jcem.91.2.9994

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Generally speaking, stress means pressure or strain. Life constantly subjects us to pressures. In people, stress can be physical (e.g., disease), emotional (e.g., grief), or psychological (e.g., fear).

Individuals vary in their ability to cope with stress. How you see a situation and your general physical health are the two major factors that determine how you will respond to a stressful event or to repeated stress.

Genes and things that happen to you early in life (e.g., child abuse or neglect), even in the womb, can affect how you handle stressful situations, possibly making you more likely to over-react. Overeating, smoking, drinking, and not exercising, which can often result from being under stress, can also add to the negative effects of stress.

Allostasis is the process of how the body responds to stress, whether it is acute (short-term) or chronic (long-term).

The best-known acute stress response is the “fight or flight” reaction that happens when you feel threatened. In this case, the stress response causes the body to release several stress hormones (e.g., cortisol and adrenaline) into the bloodstream. These hormones intensify your concentration, ability to react, and strength. Also, your heart rate and blood pressure increase, and your immune system and memory are shaper. After you have dealt with the short-term stress, your body returns to normal.

Chronic or long-term stress, however, poses a problem. If you repeatedly face challenges and your body is constantly producing higher levels of hormones, it doesn’t have time to recover. Stress hormones build up in the blood and, over time, can cause serious health problems.

Digestive system. Stomach ache is common due to a slow down in the emptying of the stomach; also diarrhea due to more activity in the colon.

Obesity. Increase in appetite, which can lead to weigh gain. (Being overweight or obese puts you at risk for diabetes and cardiovascular disease.)

Immune system. Weakening of the immune system so that you are more likely to have colds and other infections.

Nervous system. Anxiety, depression, loss of sleep and lack of interest in physical activity. Memory and decision-making can also be affected.

Cardiovascular system. Increase in blood pressure, heart rate, and blood fats (cholesterol and triglycerides). Also, increase in blood sugar (glucose) levels (especially in evening hours) and appetite (which contributes to weight gain). A(ll of these effects are risk factors for heart disease, atherosclerosis and stroke, as well as obesity and diabetes.)

Fatigue, depression

Chest pain or pressure, rapid heartbeat

Dizziness, shakiness, difficulty breathing

Menstrual cycle irregularities, erectile dysfunction (impotence), loss of libido (sex drive)

These symptoms may also lead to loss of appetite, overeating and poor sleep, all of which can have serious consequences for your health.

Usually these symptoms are minor and may be relieved through coping skills such as learning to relax, removing yourself for a time from the things that stress you out, and exercising. If the symptoms are severe, however, you may need to seek medical help to be able to identify the source of your stress and the best way to manage it.

There are practical steps you can take to cut back on stress. Regular, moderate exercise improves thought process and mood. So are relaxing, getting a good night’s sleep, and seeking emotional support from family and friends. You can also reduce the long-term effects of chronic stress by eating a healthy, low-fat diet and avoiding smoking and excessive drinking. However, if your symptoms continue or worsen, you should see your doctor.

Find-an-Endocrinologist (physician referral): www.hormone.org or call 1-800-HORMONE

Introduction to the Endocrine System, Hormones and Glands: www.hormone.org

Medline Plus (NIH): http://www.nlm.nih.gov/medlineplus/stress.html

U.S. Dept. of Health and Human Services: http://www.4woman.gov/faq/stress.htm

For more information on how to find an endocrinologist, download free publications, translate this fact sheet into other languages, or make a contribution to The Hormone Foundation, visit www.hormone.org/bilingual or call 1-800-HORMONE. The Hormone Foundation, the public education affiliate of The Endocrine Society ( www.endo-society.org ), serves as a resource for the public by promoting the prevention, treatment, and cure of hormone-related conditions. This page may be reproduced non-commercially by health care professionals and health educators to share with patients and students. Translation by MEDI-FLAG Corp.

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What Is Stress? A Systems Perspective

Affiliations.

1 Department of Psychology, University of New Mexico, Logan Hall, 2001 Redondo Dr. NE, Albuquerque, NM 87131, USA.
2 Northern Arizona University, Flagstaff, AZ 86011-0001, USA.
3 Wayne State University, 42 W Warren Avenue, Detroit, MI 48202, USA.
4 Tufts University, 200 College Avenue, Medford, MA 02155, USA.
5 Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA.
6 University of Rhode Island, 45 Upper College Road, Kingston, RI 02881, USA.
7 Department of Biological Sciences, Auburn University, Auburn, AL 36849, USA.
PMID: 30204874
DOI: 10.1093/icb/icy114

The term "stress" is used to describe important phenomena at multiple levels of biological organization, but finding a general and rigorous definition of the concept has proven challenging. Current models in the behavioral literature emphasize the cognitive aspects of stress, which is said to occur when threats to the organism are perceived as uncontrollable and/or unpredictable. Here we adopt the perspective of systems biology and take a step toward a general definition of stress by unpacking the concept in light of control theory. Our goal is to clarify the concept so as to facilitate integrative research and formal analysis. We argue that stress occurs when a biological control system detects a failure to control a fitness-critical variable, which may be either internal or external to the organism. Biological control systems typically include both feedback (reactive, compensatory) and feedforward (predictive, anticipatory) components; their interplay accounts for the complex phenomenology of stress in living organisms. The simple and abstract definition we propose applies to animals, plants, and single cells, highlighting connections across levels of organization. In the final section of the paper we explore some extensions of our approach and suggest directions for future research. Specifically, we discuss the classic concepts of conditioning and hormesis and review relevant work on cellular stress responses; show how control theory suggests the existence of fundamental trade-offs in the design of stress responses; and point to potential insights into the effects of novel environmental conditions, including those resulting from anthropogenic change.

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Can dogs serve as stress mediators to decrease salivary cortisol levels in a population of liberal arts college undergraduate students? Jimenez AG, Calderaro L, Clark S, Elacqua D, Hazen E, Lam V, Leightheiser GS. Jimenez AG, et al. Explore (NY). 2023 May-Jun;19(3):283-289. doi: 10.1016/j.explore.2022.08.007. Epub 2022 Aug 15. Explore (NY). 2023. PMID: 35989236

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Stress is a normal reaction to everyday pressures, but can become unhealthy when it upsets your day-to-day functioning. Stress involves changes affecting nearly every system of the body, influencing how people feel and behave.

By causing mind–body changes, stress contributes directly to psychological and physiological disorder and disease and affects mental and physical health, reducing quality of life.

Adapted from the APA Dictionary of Psychology

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Mind and Body Approaches for Stress and Anxiety: What the Science Says

Clinical Guidelines, Scientific Literature, Info for Patients: Mind and Body Approaches for Stress and Anxiety

.header_greentext{color:green!important;font-size:24px!important;font-weight:500!important;}.header_bluetext{color:blue!important;font-size:18px!important;font-weight:500!important;}.header_redtext{color:red!important;font-size:28px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;font-size:28px!important;font-weight:500!important;}.header_purpletext{color:purple!important;font-size:31px!important;font-weight:500!important;}.header_yellowtext{color:yellow!important;font-size:20px!important;font-weight:500!important;}.header_blacktext{color:black!important;font-size:22px!important;font-weight:500!important;}.header_whitetext{color:white!important;font-size:22px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;}.Green_Header{color:green!important;font-size:24px!important;font-weight:500!important;}.Blue_Header{color:blue!important;font-size:18px!important;font-weight:500!important;}.Red_Header{color:red!important;font-size:28px!important;font-weight:500!important;}.Purple_Header{color:purple!important;font-size:31px!important;font-weight:500!important;}.Yellow_Header{color:yellow!important;font-size:20px!important;font-weight:500!important;}.Black_Header{color:black!important;font-size:22px!important;font-weight:500!important;}.White_Header{color:white!important;font-size:22px!important;font-weight:500!important;} Relaxation Techniques

Relaxation techniques may be helpful in managing a variety of stress-related health conditions, including anxiety associated with ongoing health problems and in those who are having medical procedures. Evidence suggests that relaxation techniques may also provide some benefit for symptoms of post-traumatic stress disorder (PTSD) and may help reduce occupational stress in health care workers. For some of these conditions, relaxation techniques are used as an adjunct to other forms of treatment.

What Does the Research Show?

Biofeedback for anxiety and depression in children. A 2018 systematic review included 9 studies—278 participants total—on biofeedback for anxiety and depression in children and adolescents with long-term physical conditions such as chronic pain, asthma, cancer, and headache. The review found that, although biofeedback appears promising, at this point it can’t be recommended for clinical use in place of or in addition to current treatments.
Heart rate variability biofeedback. A 2017 meta-analysis looked at 24 studies—484 participants total—on heart rate variability (HRV) biofeedback and general stress and anxiety. The meta-analysis found that HRV biofeedback is helpful for reducing self-reported stress and anxiety, and the researchers saw it as a promising approach with further development of wearable devices such as a fitness tracker.
Progressive muscle relaxation. A 2015 systematic review , which included two studies on progressive muscle relaxation in adults older than 60 years of age, with a total of 275 participants, found that progressive muscle relaxation was promising for reducing anxiety and depression. The positive effects for depression were maintained 14 weeks after treatment.
PTSD. A 2018 meta-analysis of 50 studies involving 2,801 participants found that relaxation therapy seemed to be less effective than cognitive behavioral therapy for PTSD and obsessive-compulsive disorder. No difference was found between relaxation therapy and cognitive behavioral therapy for other anxiety disorders, including generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobias. The review noted, however, that most studies had a high risk of bias, and there was a small number of studies for some of the individual disorders.
Anxiety in people with cancer. In the 2023 joint guideline issued by the Society for Integrative Oncology and the American Society for Clinical Oncology on integrative oncology care of symptoms of anxiety and depression in adults with cancer, relaxation therapies may be offered to people with cancer to improve anxiety symptoms during active treatment (Type: Evidence based; Quality of evidence: Intermediate; benefits outweigh harms; Strength of recommendation: Moderate).
Relaxation techniques are generally considered safe for healthy people. In most research studies, there have been no reported negative side effects. However, occasionally, people report negative experiences such as increased anxiety, intrusive thoughts, or fear of losing control.
There have been rare reports that certain relaxation techniques might cause or worsen symptoms in people with epilepsy or certain psychiatric conditions, or with a history of abuse or trauma.

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A range of research has examined the relationship between exercise and depression. Results from a much smaller body of research suggest that exercise may also affect stress and anxiety symptoms. Even less certain is the role of yoga, tai chi, and qigong—for these and other psychological factors. But there is some limited evidence that yoga, as an adjunctive therapy, may be helpful for people with anxiety symptoms.

Yoga for children and adolescents. Findings from a 2021 meta-analysis and systematic review of 10 trials involving a total of 1,244 adolescents suggest a potential beneficial effect of tai chi and qigong on reducing anxiety and depression symptoms, and reducing cortisol level in adolescents. However, nonsignificant effects were found for stress, mood, and self-esteem. A 2020 systematic review of 27 studies involving the effects of yoga on children and adolescents with varying health statuses, and with varying intervention characteristics, found that in studies assessing anxiety and depression, 58 percent showed reductions in both symptoms, while 25 percent showed reductions in anxiety only. Additionally, 70 percent of studies included in the review that assessed anxiety alone showed improvements. However, the reviewers noted that the studies included in the review were of weak-to-moderate methodological quality.
Yoga, tai chi, and qigong for anxiety. A 2019 review concluded that yoga as an adjunctive therapy facilitates treatment of anxiety disorders, particularly panic disorder. The review also found that tai chi and qigong may be helpful as adjunctive therapies for depression, but effects are inconsistent.
Yoga for anxiety. A 2021 randomized controlled trial examined whether Kundalini yoga and cognitive behavioral therapy (CBT) for generalized anxiety disorder (GAD) were each more effective than a control condition (stress education) and whether yoga was inferior to CBT for the treatment GAD. The trial found that Kundalini yoga was more efficacious for generalized anxiety disorder than the control, but the results support CBT remaining first-line treatment. A 2018 systematic review and meta-analysis of 8 studies of yoga for anxiety (involving 319 participants with anxiety disorders or elevated levels of anxiety) found evidence that yoga might have short-term benefits in reducing the intensity of anxiety. However, when only people with diagnosed anxiety disorders were included in the analysis, there was no benefit.
Yoga is generally considered a safe form of physical activity for healthy people when performed properly, under the guidance of a qualified instructor. However, as with other forms of physical activity, injuries can occur. The most common injuries are sprains and strains. Serious injuries are rare. The risk of injury associated with yoga is lower than that for higher impact physical activities.
Older people may need to be particularly cautious when practicing yoga. The rate of yoga-related injuries treated in emergency departments is higher in people age 65 and older than in younger adults.

.header_greentext{color:green!important;font-size:24px!important;font-weight:500!important;}.header_bluetext{color:blue!important;font-size:18px!important;font-weight:500!important;}.header_redtext{color:red!important;font-size:28px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;font-size:28px!important;font-weight:500!important;}.header_purpletext{color:purple!important;font-size:31px!important;font-weight:500!important;}.header_yellowtext{color:yellow!important;font-size:20px!important;font-weight:500!important;}.header_blacktext{color:black!important;font-size:22px!important;font-weight:500!important;}.header_whitetext{color:white!important;font-size:22px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;}.Green_Header{color:green!important;font-size:24px!important;font-weight:500!important;}.Blue_Header{color:blue!important;font-size:18px!important;font-weight:500!important;}.Red_Header{color:red!important;font-size:28px!important;font-weight:500!important;}.Purple_Header{color:purple!important;font-size:31px!important;font-weight:500!important;}.Yellow_Header{color:yellow!important;font-size:20px!important;font-weight:500!important;}.Black_Header{color:black!important;font-size:22px!important;font-weight:500!important;}.White_Header{color:white!important;font-size:22px!important;font-weight:500!important;} Meditation and Mindfulness-Based Stress Reduction

Some research suggests that practicing meditation may reduce blood pressure, anxiety and depression, and insomnia.

Mindfulness-based stress reduction. A 2023 randomized controlled trial involving 208 participants found that mindfulness-based stress reduction (MBSR) is noninferior to escitalopram, a commonly used first-line psychopharmacologic treatment for anxiety disorders. A 2021 randomized controlled trial of 108 adults with generalized social anxiety disorder found that cognitive behavioral group therapy and MBSR may be effective treatments with long-term benefits for patients with social anxiety networks that recruit cognitive and attention-regulation brain networks. The researchers noted that cognitive behavioral therapy and MBSR may both enhance reappraisal and acceptance emotion regulation strategies.
Mindfulness-based meditation. A 2019 review concluded that as monotherapy or an adjunctive therapy, mindfulness-based meditation has positive effects on depression, and its effects can last for 6 months or more. Although positive findings are less common in people with anxiety disorders, the evidence supports adjunctive use. A 2019 analysis of 29 studies (3,274 total participants) showed that use of mindfulness-based practices among people with cancer significantly reduced psychological distress, fatigue, sleep disturbance, pain, and symptoms of anxiety and depression. However, most of the participants were women with breast cancer, so the effects may not be similar for other populations or other types of cancer. A 2014 meta-analysis of 47 trials in 3,515 participants suggests that mindfulness meditation programs show moderate evidence of improving anxiety and depression. But the researchers found no evidence that meditation changed health-related behaviors affected by stress, such as substance abuse and sleep.
Mindfulness-based programs for workplace stress. A 2018 systematic review and meta-analysis of nine studies examined mindfulness-based programs with an employee sample, which targeted workplace stress or work engagement, and measured a physiological outcome. The review found that mindfulness-based interventions may be a promising avenue for improving physiological indices of stress.
Meditation is generally considered to be safe for healthy people.
A 2019 review found no apparent negative effects of mindfulness-based interventions and concluded that their general health benefits justify their use as adjunctive therapy for patients with anxiety disorders.

.header_greentext{color:green!important;font-size:24px!important;font-weight:500!important;}.header_bluetext{color:blue!important;font-size:18px!important;font-weight:500!important;}.header_redtext{color:red!important;font-size:28px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;font-size:28px!important;font-weight:500!important;}.header_purpletext{color:purple!important;font-size:31px!important;font-weight:500!important;}.header_yellowtext{color:yellow!important;font-size:20px!important;font-weight:500!important;}.header_blacktext{color:black!important;font-size:22px!important;font-weight:500!important;}.header_whitetext{color:white!important;font-size:22px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;}.Green_Header{color:green!important;font-size:24px!important;font-weight:500!important;}.Blue_Header{color:blue!important;font-size:18px!important;font-weight:500!important;}.Red_Header{color:red!important;font-size:28px!important;font-weight:500!important;}.Purple_Header{color:purple!important;font-size:31px!important;font-weight:500!important;}.Yellow_Header{color:yellow!important;font-size:20px!important;font-weight:500!important;}.Black_Header{color:black!important;font-size:22px!important;font-weight:500!important;}.White_Header{color:white!important;font-size:22px!important;font-weight:500!important;} Hypnotherapy

Hypnosis has been studied for anxiety related to medical or dental procedures. Some studies have had promising results, but the overall evidence is not conclusive.

A 2022 systematic review and meta-analysis of 19 trials found positive effects of hypnotherapy for reducing dental anxiety and fear during dental treatment. However, the reviewers noted that despite positive effects of hypnotic interventions in the systematic review, the results of the meta-analysis are very heterogeneous.
The 2023 joint guideline issued by the Society for Integrative Oncology and the American Society for Clinical Oncology recommends that hypnosis may be offered to people with cancer to improve anxiety symptoms during cancer-related diagnostic and treatment procedures (Type: Evidence based; Quality of evidence: Intermediate; benefits outweigh harms; Strength of recommendation: Moderate).
Hypnosis is a safe technique when practiced by a trained, experienced, licensed health care provider.

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Annual Review of Psychology

Volume 72, 2021, review article, stress and health: a review of psychobiological processes.

Daryl B. O'Connor 1 , Julian F. Thayer 2 , and Kavita Vedhara 3
View Affiliations Hide Affiliations Affiliations: 1 School of Psychology, University of Leeds, Leeds LS2 9JT, United Kingdom; email: [email protected] 2 Department of Psychological Science, School of Social Ecology, University of California, Irvine, California 92697, USA; email: [email protected] 3 Division of Primary Care, School of Medicine, University of Nottingham, Nottingham NG7 2UH, United Kingdom; email: [email protected]
Vol. 72:663-688 (Volume publication date January 2021) https://doi.org/10.1146/annurev-psych-062520-122331
First published as a Review in Advance on September 04, 2020
Copyright © 2021 by Annual Reviews. All rights reserved

The cumulative science linking stress to negative health outcomes is vast. Stress can affect health directly, through autonomic and neuroendocrine responses, but also indirectly, through changes in health behaviors. In this review, we present a brief overview of ( a ) why we should be interested in stress in the context of health; ( b ) the stress response and allostatic load; ( c ) some of the key biological mechanisms through which stress impacts health, such as by influencing hypothalamic-pituitary-adrenal axis regulation and cortisol dynamics, the autonomic nervous system, and gene expression; and ( d ) evidence of the clinical relevance of stress, exemplified through the risk of infectious diseases. The studies reviewed in this article confirm that stress has an impact on multiple biological systems. Future work ought to consider further the importance of early-life adversity and continue to explore how different biological systems interact in the context of stress and health processes.

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Stress Research

“The difficulty in science is often not so much how to make the discovery but rather to know that one has made it.”

– J.D. Bernal

Causes & Sources of Stress

Living conditions, the political climate, financial insecurity, and work issues are some stressors US adults cite as the cause of their stress. Ineffective communications increase work stress to the point of frustration that workers want to quit. These stressors, unfortunately, are not something people can just ignore. Quitting a job would result in debt and financial instability which, in turn, would be added stressors.

35% of workers say their boss is a cause of their workplace stress.
80% of US workers experience work stress because of ineffective company communications.
39% of North American employees report their workload the main source of the work stress.
49% of 18 – 24 year olds who report high levels of stress felt comparing themselves to others is a stressor.
71% of US adults with private health insurance say the cost of healthcare causes them stress while 53% with public insurance say the same.
54% of Americans want to stay informed about the news but following the news causes them stress.
42% of US adults cite personal debt as a source of significant stress.
1 in 4 American adults say discrimination is a significant source of stress.
Mass shootings are a significant source of stress across all races; 84% of Hispanic report this, the highest among the races.

Stress Statistics

Two years after the World Health Organization declared COVID-19 a global pandemic, inflation, money issues and the war in Ukraine have pushed U.S. stress to alarming levels, according to polls conducted for the American Psychological Association.

A late-breaking poll, fielded March 1-3 by The Harris Poll on behalf of APA, revealed striking findings, with more adults rating inflation and issues related to the invasion of Ukraine as stressors than any other issue asked about in the 15-year history of the Stress in AmericaTM poll. This comes on top of money stress at the highest recorded level since 2015, according to a broader Stress in America poll fielded last month.

Top sources of stress were the rise in prices of everyday items due to inflation (e.g., gas prices, energy bills, grocery costs, etc.) (cited by 87%), followed by supply chain issues (81%), global uncertainty (81%), Russia’s invasion of Ukraine (80%) and potential retaliation from Russia (e.g., in the form of cyberattacks or nuclear threats) (80%).

Adults also reported separation and conflict as causes for straining and/or ending of relationships. Half of adults (51%, particularly essential workers at 61%) said they have loved ones they have not been able to see in person in the past two years as a result of the COVID-19 pandemic. Strikingly, more than half of all U.S. adults (58%) reported experiencing a relationship strain or end as a result of conflicts related to the COVID-19 pandemic, including canceling events or gatherings due to COVID-19 concerns (29%); difference of opinion over some aspect of vaccines (25%); different views of the pandemic overall (25%); and difference of opinion over mask-wearing (24%).

30% of Us adults eat comfort food “more than the usual” when faced with a challenging or stressful event.
51% of US adults engage in prayer—a routine activity—when faced with a challenge or stressful situation.
Coping mechanisms of Gen Z and Millenials experiencing stress in the US 44% of Gen Z and 40% of Millenials sleep in while exercising counts for 14% and 20% respectively.
49% of US adults report enduring stressful situations as a coping behavior to handle stress.
Less than 25% of those with depression worldwide have access to mental health treatments.

Sources: CompareCamp, American Psychological Association

Stress Management Statistics

A look at the stress management techniques employed by US adults to deal with their stress, an overwhelming majority are self-care practices. Though very helpful, it does not address the stressor at the root of the problem. Stress management programs would be beneficial not only for employees but for the company in the long run.

Stress Research from the National Library of Medicine

Stress and Cardiovascular Disease
Stress and Cancer
Stress and Diabetes
Post Traumatic Stress Disorder
Stress and Aging
Stress in Adolenscents
Stress and Meditation
Stress and Yoga
Workplace Stress

Cardiac Coherence and Post-traumatic Stress Disorder in Combat Veterans

Jay P. Ginsberg, Ph.D.; Melanie E. Berry, M.S.; Donald A Powell, Ph.D.

Alternative Therapies in Health and Medicine, A Peer-Reviewed Journal, 2010;16 (4):52-60. PDF version of the complete paper: Cardiac Coherence and PTSD in Combat Veterans

The Effect of a Biofeedback-based Stress Management Tool on Physician Stress: A Randomized Controlled Clinical Trial

Jane B. Lemaire, Jean E. Wallace, Adriane M. Lewin, Jill de Grood, Jeffrey P. Schaefer

Open Medicine 2011; 5(4)E154. PDF version of the complete paper

Coherence Training In Children With Attention-Deficit Hyperactivity Disorder: Cognitive Functions and Behavioral Changes

Anthony Lloyd, Ph.D.; Davide Brett, B.Sc.; Ketith Wesnes, Ph.D.

Alternative Therapies in Health and Medicine, A Peer-Reviewed Journal, 2010; 16 (4):34-42. PDF version of the complete paper

Coherence and Health Care Cost – RCA Actuarial Study: A Cost-Effectiveness Cohort Study

Woody Bedell; Mariette Kaszkin-Bettag, Ph.D.

Alternative Therapies in Health and Medicine, A Peer-Reviewed Journal, 2010;16 (4):26-31. PDF version of the complete paper

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Stress Statistics And Facts In 2024

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U.s. stress statistics at a glance, how many people around the world are living with stress, prevalence of stress in the u.s., workplace stress statistics, stress relief statistics.

Stress is a common issue that affects millions of people every day [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. . Due to its subjective nature, stress can drastically vary from person to person. How someone chooses to manage or cope with stress will also vary by person. However, if not properly managed, chronic stress can have a negative impact on both physical and mental health, and can ultimately increase the risk of developing serious health conditions, such as depression and stroke [2] Stress effects on the body . American Psychological Association. Accessed 12/2/2023. .

Recognizing and understanding the prevalence and potential effects of stress are crucial steps toward managing it effectively. Read on to learn more about how many people are affected by stress and possible strategies for dealing with it.

According to the American Psychological Association (APA)’s Stress in America 2022 survey results, money is a major source of stress for 66% of adults, with 57% stating current expenses, such as food and rent, as their main source of money-related stress. The remaining 43% of this group state saving for the future as their main source of money-related stress [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
Approximately 75% of U.S. adults feel that violence and crime are significant sources of stress in their lives [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
Around 34% of adults report feeling that stress is completely overwhelming for them on most days [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
The same 2022 survey from the APA found that 21% of U.S. adults report experiencing forgetfulness, 20% report an inability to concentrate and 17% report difficulty making decisions in the last month as a result of stress [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .

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According to 2021 Gallup survey data from adults in 122 countries, 41% of adults worldwide report experiencing a lot of stress [3] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
Compared to other countries, 2022 data from Gallup shows that Afghanistan currently has the highest reported stress level at 68%— the U.S. is not too far behind at 53% [4] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
According to 2022 survey data from Pew Research Center, 29% of U.S. parents reported that being a parent is stressful all or most of the time [5] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
A 2018 study of stress levels in the U.K. throughout that year found that 74% of people reported feeling so stressed they were overwhelmed or unable to cope [6] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .

“Stress is an exceedingly common experience that affects people across various life situations. Studies consistently show that a significant portion of the population experiences stress regularly, as it’s an unavoidable aspect of modern life, whether related to work, relationships, financial concerns or health issues,” explains Ryan Sultan, M.D., a board-certified psychiatrist and professor of clinical psychiatry at Columbia University.

“And unfortunately, the prevalence of stress has heightened in recent times, which can be attributed to factors like financial strain, inflation and low job security. The impact of COVID-19 has further escalated stress levels, with job losses and business closures adding to the challenges,” adds Linda Girimonte-Thompson, a licensed mental health counselor and owner of Therapy Beyond Healing, a private therapy practice located in West Sayville, New York.

37% of U.S. adults report being unable to do anything when they are stressed [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
56% of employed U.S. adults report job stability as a source of stress [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
Around 27% of U.S. adults report feeling so stressed they can’t function on most days [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
Violence and crime are a significant source of stress for 75% of U.S. adults [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
Younger U.S. women are more likely to report feeling overwhelmed by stress than older women, with 62% of women ages 18 to 34 reporting feeling completely overwhelmed by stress most days, compared to 48% of women ages 35 to 44, 27% of women 45 to 64 and 9% of women 65 years and older [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
Younger U.S. men are more likely to report feeling overwhelmed by stress than older men, with 51% of men ages 18 to 34 reporting feeling completely overwhelmed by stress most days, compared to 48% of men ages 35 to 44, 21% of men 45 to 64 and 8% of men 65 years and older [1] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .

“Various factors contribute to the increased stress levels of the U.S. population, such as the fast-paced nature of modern life, technological advancements and societal expectations. People today often juggle multiple responsibilities and face constant stimuli, leading to heightened stress levels compared to previous generations,” says Dr. Sultan. However, in the past several years, the U.S. population has also experienced an increase in external stressors, such as inflation, violence and political divisiveness, according to the APA.

According to the APA’s 2023 Work in America Survey, 77% of workers reported experiencing work-related stress in the past month, with 57% of those citing negative impacts as a result, such as emotional exhaustion and lack of motivation to do their best [7] World Unhappier, More Stressed Out Than Ever . Gallup. Accessed 12/2/2023.. .
These 2023 APA survey results also found that respondents lacking meaningful work (71%) had a higher likelihood of reporting that they were typically stressed or tensed throughout the workday, with just 45% of those who reported having meaningful work stating the same [7] World Unhappier, More Stressed Out Than Ever . Gallup. Accessed 12/2/2023.. .
A 2021 Italian study compared the stress levels of males and females who reported medium to high stress levels upon returning to work after being unemployed and found that females (22.7%) were more likely to report high stress levels than males (11%) [8] What Is the World's Emotional Temperature? . Gallup. Accessed 1/5/2024. .

According to the World Health Organization (WHO), work-related stress often occurs when people are presented with work demands and pressures outside of their knowledge or comfort zone. “Long working hours, tight deadlines and an ever-increasing competition for success can also contribute to a highly stressful work environment,” shares Dr. Sultan.

“The shift to remote work during COVID[-19] was a positive development in regards to stress, allowing for a slowdown, but returning to the office may have induced additional stress and anxiety for some individuals,” states Girimonte-Thompson, who recommends utilizing company wellness programs or emphasizing work-life balance when possible in an effort to reduce work-related stress.

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According to a 2019 study that explored the effects of nature experiences on stress, nature experiences that lasted 21 minutes to 30 minutes had the greatest reduction in stress levels with an 18.5% per hour drop in cortisol levels for the duration of the nature experience [9] Parenting in America Today . Pew Research Center. Accessed 1/5/2024. .
Approximately 42% of adults report going online to help manage their stress. However, only 29% of these people say that going online is very or extremely effective in managing stress [10] Stress: statistics . Mental Health Foundation. Accessed 12/2/2023.. .
According to 2022 survey results from the American Heart Association, 95% of dog and cat owners rely on their pet for stress relief [11] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .
The same survey found that approximately 70% of pet owners report they prefer to spend time with their pet over watching television to reduce stress [11] Stress in America 2022: Concerned for the future, beset by inflation . American Psychological Association. Accessed 12/2/2023. .

If not properly managed, stress can negatively impact multiple bodily systems and contribute to a range of health concerns, including:

Muscle tension
Upset stomach
Trouble sleeping
Changes in appetite
Shortness of breath or rapid breathing

Long-term effects of stress can include:

Chronic fatigue
Hypertension
Heart attack
Stroke [2] Stress effects on the body . American Psychological Association. Accessed 12/2/2023.

However, Dr. Sultan explains that it’s not just about coping with chronic stress, it’s also important to manage occasional stressors as even occasional stress can impact one’s mental and physical health. Although effective stress-relief techniques will be dependent on the individual, activities such as mindfulness practices , exercise or hobbies, can significantly mitigate the adverse effects of stress.

While societal, personal and work-related factors significantly contribute to stress levels, it’s crucial for individuals to actively seek and employ stress-relief techniques that will work for them. By understanding and addressing the sources of stress, and by promoting and practicing effective management strategies, individuals can help reduce their stress levels and lower their risk for serious long-term health conditions.

Stress in America 2022: Concerned for the future, beset by inflation. American Psychological Association. Accessed 12/2/2023.
Stress effects on the body. American Psychological Association. Accessed 12/2/2023.
World Unhappier, More Stressed Out Than Ever. Gallup. Accessed 12/2/2023..
What Is the World's Emotional Temperature?. Gallup. Accessed 1/5/2024.
Parenting in America Today. Pew Research Center. Accessed 1/5/2024.
Stress: statistics. Mental Health Foundation. Accessed 12/2/2023..
2023 Work in America Survey. American Psychological Association. Accessed 1/5/2024.
Costa C, Briguglio G, Mondello S, et al. Perceived Stress in a Gender Perspective: A Survey in a Population of Unemployed Subjects of Southern Italy. Frontiers in Public Health. 2021;9:640454.
Hunter MR, Gillespie BW, Chen SYP. Urban Nature Experiences Reduce Stress in the Context of Daily Life Based on Salivary Biomarkers. Frontiers in Psychology. 2019;10:413490.
Stress and Exercise. American Psychological Association. Accessed 1/9/2024..
New survey: 95% of pet parents rely on their pet for stress relief. American Heart Association. Accessed 12/3/2023.
Stress. Mental Health Foundation. Accessed 12/2/2023.
More than a quarter of U.S. adults say they’re so stressed they can’t function. American Psychological Association. Accessed 12/2/2023.
Occupational health: Stress at the workplace. World Health Organization. Accessed 12/3/2023.
Stress in America 2020. American Psychological Association. Accessed 12/3/2023.
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Experimental research on the low-cycle fatigue crack growth rate for a stiffened plate of eh36 steel for use in ship structures.

1. Introduction

2. low cycle fatigue crack growth experiment for stiffened plate, 3. result and discussion, 3.1. experimental results of stiffened plates with single-edge crack, 3.2. experimental results of stiffened plates with central crack, 4. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Click here to enlarge figure

Elastic Modulus/GPa	Poisson’s Ratio	Yield Stress/MPa	Ultimate Tensile Strength/MPa
206	0.3	434.94	548.91

Specimen Number	P /kN	R = P /P	Nominal Stress/MPa	Crack Location	Stiffener Height
P1	84.24	−1	120	single-edge crack	30 mm
P2	90.72	−1	130	single-edge crack	30 mm
P3	97.20	−1	140	single-edge crack	30 mm
P4	384.00	0.031	280	central crack	30 mm
P5	420.00	0.2	300	central crack	30 mm
P6	420.00	0.2	300	central crack	0 mm

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Share and Cite

Dong, Q.; Xu, G.; Chen, W. Experimental Research on the Low-Cycle Fatigue Crack Growth Rate for a Stiffened Plate of EH36 Steel for Use in Ship Structures. J. Mar. Sci. Eng. 2024 , 12 , 1365. https://doi.org/10.3390/jmse12081365

Dong Q, Xu G, Chen W. Experimental Research on the Low-Cycle Fatigue Crack Growth Rate for a Stiffened Plate of EH36 Steel for Use in Ship Structures. Journal of Marine Science and Engineering . 2024; 12(8):1365. https://doi.org/10.3390/jmse12081365

Dong, Qin, Geng Xu, and Wei Chen. 2024. "Experimental Research on the Low-Cycle Fatigue Crack Growth Rate for a Stiffened Plate of EH36 Steel for Use in Ship Structures" Journal of Marine Science and Engineering 12, no. 8: 1365. https://doi.org/10.3390/jmse12081365

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ORIGINAL RESEARCH article

Study on fatigue characteristics of red sandstone under extremely high stress in the hydro-chemical environment.

1 Chengdu Surveying Geotechnical Research Institute Co., Ltd. of MCC, Chengdu, China
2 Chongqing University, Chongqing, China

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To study the failure of red sandstone under extremely high stress during the service life of tunnels, an in-depth study was conducted on the mechanical properties of red sandstone under uniaxial loading and cyclic loading and unloading processes at different pH values using the AG-250kNIS electronic precision material testing machine and MTS815 mechanical testing machine. The results show that as the acidity and alkalinity increase, the peak stress under uniaxial loading decreases and the axial strain increases,The peak stress at failure is 9.40 MPa, 12.37 MPa, 7.18 MPa, and 5.36 MPa, respectively, accounting for 74.19%, 68.91%, 40.38%, and 36.21% of the uniaxial compressive strength; The number of cycles significantly decreases during cyclic loading and unloading fatigue failure, and the stress required for sandstone failure gradually decreases. The peak strength and elastic modulus of sandstone show a decreasing trend, indicating that the hydrochemical environment plays an accelerating role in rock degradation. During the cyclic loading and unloading process of sandstone, there is a continuous increase in dissipated energy and finally a sudden increase, the d U / U and e U / U ratios at the peak point of sandstone in the natural state are 0.399 and 0.601, respectively, while the overall elastic energy shows an increasing trend; and a damage evolution model was established based on dissipative energy, which can better describe the degradation process of red sandstone.

Keywords: Red sandstone, Fatigue loading, Tunnel safety maintenance, Damage characteristics, hydro-chemical environment

Received: 22 Jun 2024; Accepted: 12 Aug 2024.

Copyright: © 2024 Peng, Ren, He, Li, Wu and Zhou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Fei Wu, Chongqing University, Chongqing, China

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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About 400 Million People Worldwide Have Had Long Covid, Researchers Say

The condition has put significant strain on patients and society — at a global economic cost of about $1 trillion a year, a new report estimates.

Bright red cots are arranged in neat rows on the National Mall lawn, each with a decorated pillow. A pillow in the foreground reads “I deserve care” and “#post-covid.”

By Pam Belluck

Pam Belluck has been reporting about long Covid since the condition first emerged.

Share full article

About 400 million people worldwide have been afflicted with long Covid, according to a new report by scientists and other researchers who have studied the condition. The team estimated that the economic cost — from factors like health care services and patients unable to return to work — is about $1 trillion worldwide each year, or about 1 percent of the global economy.

The report, published Friday in the journal Nature Medicine, is an effort to summarize the knowledge about and effects of long Covid across the globe four years after it first emerged.

It also aims to “provide a road map for policy and research priorities,” said one author, Dr. Ziyad Al-Aly, the chief of research and development at the V.A. St. Louis Health Care System and a clinical epidemiologist at Washington University in St. Louis. He wrote the paper with several other leading long Covid researchers and three leaders of the Patient-Led Research Collaborative, an organization formed by long Covid patients who are also professional researchers.

Among the conclusions:

About 6 percent of adults globally have had long Covid.

The authors evaluated scores of studies and metrics to estimate that as of the end of 2023, about 6 percent of adults and about 1 percent of children — or about 400 million people — had ever had long Covid since the pandemic began. They said the estimate accounted for the fact that new cases slowed in 2022 and 2023 because of vaccines and the milder Omicron variant.

They suggested that the actual number might be higher because their estimate included only people who developed long Covid after they had symptoms during the infectious stage of the virus, and it did not include people who had more than one Covid infection.

Many people have not fully recovered.

The authors cited studies suggesting that only 7 percent to 10 percent of long Covid patients fully recovered two years after developing long Covid. They added that “some manifestations of long Covid, including heart disease, diabetes, myalgic encephalomyelitis and dysautonomia are chronic conditions that last a lifetime.”

The consequences are far-reaching, the authors wrote: “Long Covid drastically affects patients’ well-being and sense of self, as well as their ability to work, socialize, care for others, manage chores and engage in community activities — which also affects patients’ families, caregivers and their communities.”

The report cited estimates that between two million and four million adults were out of work because of long Covid in 2022 and that people with long Covid were 10 percent less likely to be employed than those who were never infected with the virus. Long Covid patients often have to reduce their work hours, and one in four limit activities outside work in order to continue working, the report said.

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How to Relax in Stressful Situations: A Smart Stress Reduction System

Yekta said can.

1 Computer Engineering Department, Bogazici University, 34342 Istanbul, Turkey; [email protected] (N.C.); [email protected] (D.E.); rt.ude.nuob@yosre (C.E.)

Heather Iles-Smith

2 Leeds Teaching Hospitals NHS Trust/University of Leeds, Leeds LS1 3EX, UK; [email protected]

Niaz Chalabianloo

Javier fernández-Álvarez.

3 General Psychology and Communication Psychology, Catholic University of Milan, 20123 Milan, Italy; [email protected] (J.F.-Á.); [email protected] (C.R.); [email protected] (G.R.)

Claudia Repetto

Giuseppe riva.

Stress is an inescapable element of the modern age. Instances of untreated stress may lead to a reduction in the individual’s health, well-being and socio-economic situation. Stress management application development for wearable smart devices is a growing market. The use of wearable smart devices and biofeedback for individualized real-life stress reduction interventions has received less attention. By using our unobtrusive automatic stress detection system for use with consumer-grade smart bands, we first detected stress levels. When a high stress level is detected, our system suggests the most appropriate relaxation method by analyzing the physical activity-based contextual information. In more restricted contexts, physical activity is lower and mobile relaxation methods might be more appropriate, whereas in free contexts traditional methods might be useful. We further compared traditional and mobile relaxation methods by using our stress level detection system during an eight day EU project training event involving 15 early stage researchers (mean age 28; gender 9 Male, 6 Female). Participants’ daily stress levels were monitored and a range of traditional and mobile stress management techniques was applied. On day eight, participants were exposed to a ‘stressful’ event by being required to give an oral presentation. Insights about the success of both traditional and mobile relaxation methods by using the physiological signals and collected self-reports were provided.

1. Introduction

Stress constitutes a complex process that is activated by a physical or mental threat to the individuals’ homeostasis, comprising a set of diverse psychological, physiological and behavioral responses [ 1 ]. Although it is usually considered a negative response, stress actually constitutes a key process for ensuring our survival. However, when a stress response is repeatedly triggered in the absence of a challenging stimulus, or if there is constant exposure to challenging situations, stress can become harmful. Evidence suggests that, in either of these two contexts, stress is a persistent factor for the development of psycho-pathological conditions [ 2 , 3 ].

When faced with stressful events, people make autonomic and controlled efforts to reduce the negative impact and maximize the positive impact that every specific situation may provoke. Generally, this process is denominated as emotion regulation, formally defined as the process by which individuals can influence what emotions they have, when they have them and how they experience and express those emotions [ 4 ]. It has been suggested that the term emotion regulation can be understood as a broad tag that comprises the regulation of all responses that are emotionally charged, from basic emotions to complex mood states as well as regulation of everyday life [ 5 ].

Failure to address triggers of stress has been shown to lead to chronic stress, anxiety and depression, and attributed to serious physical health conditions such as cardiovascular disease [ 6 ]. The World Health Organization concluded that psychological stress is one of the most significant health problems in the 21st-century and is a growing problem [ 7 ]. There are various interventions to minimize stress based on individual preferences and requirements. Stress management techniques including ancient practices such as Tai Chi [ 8 ] and yoga [ 9 ] as well as other physical activities [ 10 ] are often cited as being helpful in combating stress. Likewise traditional meditation, mindfulness [ 11 ] and cognitive behavioural therapy (CBT) [ 12 ] all have established benefits. These techniques are not applicable in office or social environments, or during most daily routines. Therefore, a smart device based stress management application may be of benefit. Recently, smartphone applications such as Calm, Pause, Heartmath and Sway have been developed for indoor environments. However, these applications are not individualized nor do they include biofeedback and studies that validate their effects are limited [ 13 ].

In this study, we used the stress level detection scheme using physiological signals and added a physical activity based context analyzer. When the user experiences a high stress level, the system suggests appropriate stress reduction methods (traditional or mobile). We further compare the effects of traditional and mobile stress alleviation methods on physiological data of 15 international Ph.D. students (participants) during eight days of training. In addition, 1440 h of physiological signals from Empatica E4 smart bands were collected in this training event. Stress management techniques based on the emotion regulation model of James Gross [ 4 ] were applied to reduce participant stress levels. To the best of our knowledge, this work is the first one suggesting appropriate stress reduction methods based on contextual information and comparing both traditional and mobile stress management interventions in the real-life environment using a commercial smart-band based automatic stress level detection system that eliminates motion artifacts. Using such a system is essential because these offline stress level detection algorithms could be used in real-time biofeedback apps.

Application of our stress level detection algorithm, in a real world context, could allow individuals to receive feedback regarding high stress levels along with recommendations for relaxation methods. Additional continued monitoring may also enable the individual to better understand the effectiveness of any stress reduction methods. However, for our stress detection algorithm to be applied in daily life, the smart device should be unobtrusive (i.e., should not be comprised of cables, electrodes, boards). Our system works on smart-bands which are perfect examples of this type of unobtrusive wearable device.

This paper describes emotion regulation in the context of stress management and how yoga and mindfulness can be used for regulating emotions ( Section 2 ). Methods of detecting stress and analyzing context based on physical activity are described ( Section 3 ) and data are presented related to our method for stress level detection with the use of smart-bands ( Section 4 ). Experimental results and discussion are also presented ( Section 5 ) and we present the conclusions and future works of the study ( Section 6 ).

The major research contributions of this study are the following:

Developing a physical activity based context analyzer and relaxation method suggestion system
Comparison of stress reduction methods (mobile mindfulness, traditional mindfulness and yoga) and their effectiveness in the context of stress management with the use of an unobtrusive smartwatch based stress level detection system
Application of James Gross’s prominent emotion regulation model in the context of stress management and measuring the physiological component with smart bands.

2. Background

2.1. emotion regulation in the context of stress management.

Stress is a normal part of daily life. However, its effects often vary across individuals and despite similar circumstances, some people do not feel under strain while others may be severely affected. Multiple reasons exist for these differences between individuals, including how people perceive reality and how they respond to the numerous stimuli to which they are exposed. When a person believes that a certain situation surpasses their available coping mechanisms, it is referred to as perceived stress. Thus, perceived stress varies from person to person depending on the value that an individual gives to a situation and their self-recognition of the resources to deal with it.

Numerous psychological scientists have investigated perceived stress. Individuals who display a mismatch between contextual demands and perceived resources constantly (rather than during a specific moment in time) are referred to as experiencing chronic stress. Chronic stress has not only been shown to be very relevant in people’s well-being and quality of life, but also important in the appearance and maintenance of several physical and mental diseases [ 14 ].

As a consequence, mounting research has focused on the mechanisms that people implement in order to alleviate the physical and cognitive burden associated with that perceived stress. Coping styles, stress management techniques, self-regulation, or emotion regulation techniques are different labels that define the way people implement certain behavioral, cognitive, or emotional strategies to maintain allosteric load [ 15 ]. In other words, every living organism needs to vary among plasticity and stability in order to survive. Human beings are not the exception to the rule and the complex system that applies to every single person and the necessity of reaching a constant level of regulation permits the individuals to pursue their goals.

Specifically, emotion regulation has been defined as the study of “the processes by which we influence which emotions we have when we have them, and how we experience and express them” [ 4 ]. A large body of evidence has shown that there are very different consequences depending on the effectiveness people achieve to regulate their emotions. Naturally, both at an implicit or explicit level, people regulate emotions in order to maintain those allosteric levels previously mentioned. Therefore, when there are specific stressors that demand a particular cognitive or physical response, the emotional reactivity may be stronger and the need for a proper regulation more relevant. Indeed, emotion regulation has shown to be a transdiagnostic factor that is present at a wide range of mental disorders. In other words, the way people initiate, implement and monitor their emotional processes, in order to reach more desirable states, has a significant impact on the stress levels. Some emotion regulation (ER) strategies have shown to be correlated with mental health issues. Among these strategies, cognitive reappraisal, problem-solving, or acceptance shall be mentioned as strategies that are negatively correlated with psychopathology, while rumination, experiential avoidance, or suppression are positively correlated with psychopathology [ 16 ]. In this regard, hinging on the different ER strategies deployed, ER can constitute a protective factor to face stress responses that all individuals experience after minor or major stressors [ 17 ]. Additionally, an adaptive regulation of emotions, by managing stress, may also be beneficial for clinical populations, such as people suffering from affective disorders [ 18 , 19 ].

Therefore, from whole psychotherapeutic treatments to single self-applied applications, studies in the literature have focused on how people can better regulate their emotions and manage their stress levels. Among many other techniques, cognitive behavioral therapy, autogenic training, biofeedback, breathing exercises, relaxation techniques, guided imagery, mindfulness, yoga, or Tai-Chi, are some of the stress management interventions that have received attention from researchers [ 20 , 21 ].

2.2. Yoga and Mindfulness: As Tools for Emotion Regulation

2.2.1. yoga.

Yoga is an ancient Eastern practice that developed more than 2000 years ago. Although its original creator and source are uncertain, the earliest written word ‘Yoga Sutra’ describes the philosophy of yoga focussing on growing spirituality, regulating emotions and thoughts. Initially, the focus was on awareness of breathing and breathing exercises ‘pranayama’ to calm the mind and body, ultimately reaching a higher state of consciousness.

As yoga evolved, physical movement in the form of postures was included and integrated with yogic breathing ‘prana’ and elements of relaxation. The underlying purpose is to create physical flexibility, reduce pain and unpleasant stimuli and reduce negative thoughts and emotions to calm the mind and body, thereby improving well-being. In the healthcare literature, the benefits are reported to be far-reaching both for mental and physical health conditions such as anxiety, depression, cardiovascular disease, cancer and respiratory symptoms. It is also reported to reduce muscular-skeletal problems and physical symptoms through increasing the awareness of the physical body.

Yoga has become a global phenomenon and is widely practiced in many different forms. Generally, all types of yoga include some elements of relaxation. Additionally, some forms include mainly pranayama and others are more physical in nature. One such practice is vinyasa flow which involves using the inhale and exhale of the breathing pattern to move through a variety of yoga postures; this leads to the movement becoming meditative. The practice often includes pranayama followed by standing postures linked together with a movement called vinyasa, (similar to a sun salutation) which helps to keep the body moving and increases fitness, flexibility and helps maintain linkage with the breath. The practice also often includes a range of seated postures, an inversion (such as headstand or shoulder stand) and final relaxation ‘savasana’.

2.2.2. Mindfulness

Mindfulness involves being more present at the moment by acknowledging the here and now, often referred to as ‘being present’ rather than focussing on the past or future [ 8 ]. Being present may include being aware of our surroundings and the environment, or of what we are eating and drinking and physical sensations such as the sun or wind on our skin.

Acknowledging the thoughts and body are also aspects of mindfulness. Each day humans experience thousands of thoughts, the majority being of no consequence. In some instances, these thoughts are repetitive and negative in nature which can lead to increased stress and the related unpleasant physical symptoms such as feeling anxious, nausea and tension headaches. Being mindful includes an awareness of our thinking and whether we are caught up with our thoughts rather than being aware of the moment. Additionally, on a daily basis, awareness of the physical body may be minimal; being mindful includes increasing this awareness through becoming more connected with the sensations in the body. This might include experiencing the legs moving when walking, or feeling the ground under the feet or the natural way of the body whilst standing.

Mindfulness has been shown to be of benefit to physical and mental health. It is currently recommended by the National Institute for Clinical Excellence [ 22 ] as adjunctive therapy to Cognitive Behavioural Therapy (CBT) for the prevention of relapse depression.

However, it may be challenging for some individuals to do this with a multitude of distractions around them and, therefore, they may choose to identify a particular time and place when and where they can sit in a comfortable position to start to become aware of their breathing and bodily sensations.

2.2.3. Mobile Mindfulness Inspired By Tai-Chi—Pause

Tai-Chi is an internal Chinese martial art practiced for both its defense training, its health benefits and meditation. There is good evidence of benefits for depression, cardiac and stroke rehabilitation and dementia [ 23 ]. The term Tai-Chi refers to a philosophy of the forces of yin and yang, related to the moves. An iPhone application Pause inspired by Tai-Chi is used for guided mindfulness which draws upon the principles of mindfulness meditation to trigger the body’s rest and digest response, quickly restoring attention [ 24 ].

3. Related Work

Researchers have created the ability to detect stress in laboratory environments with medical-grade devices [ 25 , 26 , 27 , 28 ]; smartwatches and smart bands started to be used for stress level detection studies [ 29 , 30 , 31 ]. These devices provide high comfort and rich functionality for the users, but their stress detection accuracies are lower than medical-grade devices due to low signal quality and difficulty obtaining data in intense physical activity. If data are collected for long periods, researchers have shown that their detection performance improves [ 32 ]. During movement periods, the signal can be lost (gap in the data) or artifacts might be generated. Stress level detection accuracies for 2-classes by using these devices are around 70% [ 29 , 30 , 33 , 34 ].

After detecting the stress level of individuals, researchers should recover from the stressed state to the baseline state. To the best of our knowledge, there are very few studies that combine automatic stress detection (using physiological data) with recommended appropriate stress management techniques. Ahani et al. [ 35 ] examined the physiological effect of mindfulness. They used the Biosemi device which acquires electroencephalogram (EEG) and respiration signals. They successfully distinguished control (non-meditative state) and meditation states with machine learning algorithms. Karydis et al. [ 36 ] identified the post-meditation perceptual states by using a wearable EEG measurement device (Muse headband). Mason et al. [ 37 ] examined the effect of yoga on physiological signals. They used PortaPres Digital Plethtsmograph for measuring blood pressure and respiration signals. They also showed the positive effect of yoga by using these signals. A further study validated the positive effect of yoga with physiological signals; researchers monitored breathing and heart rate pulse with a piezoelectric belt and a pulse sensor [ 21 ]. They demonstrated the effectiveness of different yogic breathing patterns to help participants relax. There are also several studies showing the effectiveness of mobile mindfulness apps by using physiological signals [ 20 , 38 , 39 ]. Svetlov et al. [ 20 ] monitored the heart rate variability (HRV), electrodermal activity (EDA), Salivary alpha-amylase (sAA) and EEG values. In other studies, EEG and respiration signals were also used for validating the effect of mobile mindfulness apps [ 38 , 39 ]. When the literature is examined, it could be observed that the effect of ancient relaxation methods and mobile mindfulness methods are examined separately in different studies. Ancient methods generally require out of office environments that are not suitable for most of the population, since, in the modern age, people started to spend more time in office-like environments. On the other hand, some smartphone applications such as Pause, HeartMath and Calm do not require extra hardware or equipment and be applicable in office environments. Hence, an ideal solution depends on the context of individuals. A system that monitors stress levels, analyzes the context of individuals and suggests an appropriate relaxation method in the case of high stress will benefit society. Furthermore, mobile methods along with the ancient techniques should be applied in stressful real-life events and their effectiveness should be compared by investigating physiological signals. When the literature is examined, there is not any study comparing the performance of these methods in real-life events (see Table 1 ). Another important finding is that these methods should be compared with unobtrusive wearable devices so that they could be used for a biofeedback system in daily lives. Individuals may be reluctant to use a system with cables, electrodes and boards in their daily life. Therefore, a comparison of different states with such systems could not be used in daily life. There is clearly a need for a suggestion and comparison of ancient and mobile meditation methods by using algorithms that could run on unobtrusive devices. An ideal system should detect high stress levels, suggest relaxation methods and control whether users are doing these exercises right or not with unobtrusive devices. Our algorithm is suitable to be embedded in such daily life applicable systems that use physiological signals such as skin temperature (ST), HRV, EDA and accelerometer (ACC). In this paper, we present the findings of our pilot study that tested the use of our algorithm during general daily activities, stress reduction activities and a stressful event.

Comparison of our work with the studies applying different types of meditation techniques for stress management in the literature.

Article	YOGA	Mindfulness	Mobile Relaxation	Device	Signal	Daily Suitable
Ahani et al. [ ]	X	🗸	X	Biosemi	EEG and Respiration	No
Mason et al. [ ]	🗸	X	X	Digital Plethysmograph (PortaPres)	Virtual Blood Pressure Respiration	No
Svetlov et al. [ ]	X	X	🗸	Several	HRV, EDA, sAA and EEG	No
Puranik et al. [ ]	🗸	X	X	MPU 6050 + piezoelectric belt + pulse sensor + smartphone	Heart Rate + Respiration	No
Karydis et al. [ ]	X	🗸	X	Muse Headband	EEG	No
Cheng et al. [ ]	X	X	🗸	Emotiv wireless headset	EEG	No
Ingle et al. [ ]	X	X	🗸	8-channel Enobio EEG + piezoelectric belt	EEG + Respiratory	No
Our work	🗸	🗸	🗸	Empatica E4 wristband	PPG (Photoplethysmography), EDA, ACC, ST	Yes

4. Methodology

4.1. unobtrusive stress detection system with smart bands.

Our stress detection system developed in [ 32 ] allows users to be aware of their stress levels during their daily activities without creating any interruption or restriction. The only requirement to use this system is the need to wear a smart band. Participants in this study wore the Empatica E4 smart band on their non-dominant hand. The smart band provides Blood Volume Pressure, ST, EDA, IBI (Interbeat Interval) and 3D Acceleration. The data are stored in the memory of the device. Then, the artifacts of physiological signals were detected and handled. The features were extracted from the sensory signals and fed to the machine learning algorithm for prediction. In order to use this system, pre-trained machine learning models are required. For training the models, feature vectors and collected class labels were used.

4.1.1. EDA Preprocessing Artifact Detection and Removal Methods

The body sweats when emotional arousal and stress are experienced and, therefore, skin conductance increases [ 40 ]. This makes EDA a promising candidate for stress level detection. Intense physical activity and temperature changes contaminate the SC (Skin Conductance) signal. Therefore, affected segments (artifacts) should be filtered out from the original signal. In order to detect the artifacts in the SC signal, we used an EDA toolkit [ 41 ] which is 95% accurate on the detection of the artifacts. While developing this tool, technicians labeled the artifacts manually. They trained a machine learning model by using the labels. In addition to the SC signal, 3D acceleration and ST signals were also used for artifact detection. We removed the parts that this tool detected as artifacts from our signals. We further added batch processing and segmentation to this tool by using custom software built-in Python 2.7.

4.1.2. EDA Feature Extraction Methods

After the artifact removal phase, features were extracted from the EDA signal. This signal has two components phasic and tonic; features from both components were extracted (see Table 2 ). The cvxEDA tool [ 42 ] was used for the decomposition of the signal into these components. This tool uses convex optimization to estimate the Autonomic Nervous System (ANS) activity that is based on Bayesian statistics.

EDA features and their definitions.

Feature	Description
Quartdev Tonic	Quartile deviation (75 percentile–25 percentile) of the phasic component
Strong Peaks Phasic	The number of strong peak per 100 s
Peaks Phasic	The number of peaks per 100 s
Perc20	20th percentile of the phasic component
Perc80 Tonic	80th percentile of the phasic component
Mean Tonic	Mean of the phasic component
SD Tonic	Standard deviation of phasic component

Tonic Component Features

The tonic component in the EDA signal represents the long-term slow changes. This component is also known as the skin conductance level. It could be regarded as the indicator of general psychophysiological activation [ 43 ].

Phasic Component Features

The phasic component represents faster (event-related ) differences in the SC signal. The Peaks of phasic SC component as a reaction to a stimulus is also called Skin Conductance Response [ 43 ]. After we decompose the phasic component from the EDA signal, peak related features were extracted.

4.1.3. Heart Activity Preprocessing (Artifact Detection and Removal) and Feature Extraction Methods

Heart activity (or, more specifically, HRV) reacts to changes in the autonomic nervous system (ANS) caused by stress [ 44 ] and it is, therefore, one of the most commonly used physiological signal for stress detection [ 40 ]. However, vigorous movement of subjects and improperly worn devices may contaminate the HRV signal collected from smartwatches and smart bands. In order to address this issue, we developed an artifact handling tool in MATLAB programming language [ 45 ] that has batch processing capability. First, the data were divided into 2 min long segments with 50% overlapping. Two-minute segments were selected because it is reported that the time interval for stress stimulation and recovery processes is around a few minutes [ 46 ]. The artifact detection percentage rule (also employed in Kubios [ 47 ]) was applied after the segmentation phase. In this rule, each data point was compared with the local average around it. When the difference was more than a predetermined threshold percentage, (20% is commonly selected in the literature [ 48 ]), the data point was labeled as an artifact. In our system, we deleted the inter-beat intervals detected as the artifacts and interpolated these points with the cubic spline interpolation technique which was used in the Kubios software [ 47 ]. The time-domain features of HRV are calculated. In order to calculate the frequency domain features, we interpolated the RR intervals to 4 Hz. Then, we applied the Fast Fourier Transform (FFT). These time and frequency domain features (see Table 3 ) were selected because these are the most discriminative ones in the literature [ 30 , 49 , 50 ].

HRV features and their definitions [ 32 ].

Feature	Description
Mean RR	Mean value of the inter-beat (RR) intervals
STD RR	Standard deviation of the inter-beat interval
pNN50	Percentage of the number of successive RR intervals varying more than 50 ms from the previous interval
RMSSD	Root mean square of successive difference of the RR intervals
SDSD	Related standard deviation of successive RR interval differences
HRV triangular index	Total number of RR intervals divided by the height of the histogram of all RR intervals measured on a scale with bins of 1/128 s
TINN	Triangular interpolation of RR interval histogram
LF	Power in low-frequency band (0.04–0.15 Hz)
HF	Power in high-frequency band (0.15–0.4 Hz)
pLF	Prevalent low-frequency oscillation of heart rate
pHF	Prevalent high-frequency oscillation of heart rate
VLF	Power in very low-frequency band (0.00–0.04 Hz)
LF/HF	Ratio of LF-to-HF

4.1.4. Accelerometer Feature Extraction Methods

Research has shown that movements of the human body and postures can indeed be employed as a means to detect signs of different emotional states. The dynamics of body movement were investigated by Castellano et al. who used multimodal data to identify human affective behaviors. Specific movement metrics, such as the amount of movement, intensity and fluidity, were used to help deduct emotions, and it was found that the amount of movement was a major factor in distinguishing different types of emotions [ 51 ]. Melzer et al. investigated whether movements comprised of collections of Laban movement components could be recognized as expressing basic emotions [ 52 ]. The results of their study confirm that, even when the subject has no intention of expressing emotions, particular movements can assist in the perception of bodily expressions of emotions. Accelerometer sensors may be used to detect these movements and different types of affect. The accelerometer sensor data are used for two different purposes in our system. Firstly, we extracted features from the accelerometer sensor, for detecting stress levels. We also selected the features to be used as described in Table 4 [ 53 ] and, as mentioned above, this sensor was also employed to clean the EDA signal in the EDAExplorer Tool [ 41 ].

ACC features and their definitions.

Feature	Description
Mean X	Mean acceleration over axis
Mean Y	Mean acceleration over axis
Mean Z	Mean acceleration over axis
MeanAccMag	Mean acceleration over acceleration magnitude
Energy	FFT energy over mean acceleration magnitude

4.1.5. Skin Temperature

A skin temperature signal is used for the artifact detection phase of the EDA signal in the EDAExplorer Tool [ 41 ]. After we divide our data into segments, different modalities were merged into one feature vector. The heart activity signal started with a delay (to calculate heartbeats per minute at the start) and all signals were then synchronized. We included start and end timestamps for each segment, and each modality was merged with a custom Python script.

4.1.6. Machine Learning Classifier Algorithms

The Weka machine learning toolkit [ 54 ] is used for identifying stress levels. The Weka toolkit has several preprocessing features before classification. Our data set was not balanced when the number of instances belonging to each class was considered. We solved this issue by removing samples from the majority class. We selected random undersampling because it is the most commonly applied method [ 55 ]. In this way, we prevented classifiers from biasing towards the class with more instances. In this study, we employed five different machine learning classification algorithms to recognize different stress levels: MultiLayer Perceptron (MLP), Random Forest (RF) (with 100 trees), K-nearest neighbors (kNN) ( n = 1–4), Linear discriminant analysis (LDA), Principal component analysis (PCA) and support vector machine (SVM) with a radial basis function. These algorithms were selected because they were the most commonly applied and successful classifiers for detecting stress levels [ 30 , 48 ]. In addition, 10-fold stratified cross-validation was then applied and hyperparameters of the machine learning algorithms were fine-tuned with grid search. The best performing models have been reported.

4.1.7. Dimensionality Reduction

We applied correlation-based feature selection (CBFS) technique which is available in the Weka machine learning package for combined signal [ 56 ]. The CBFS method removes the features that are less correlated with the output class. For every model, we selected the ten most important features. This method is applied for MLP, RF, kNN and LDA. In order to create an SVM based model, we applied PCA based dimensionality reduction where the covered variance is selected as 0.95 (the default setting).

4.1.8. Insights from the Feature Selection Process

The CBFS method computes the correlation of features with the ground truth label of the stress level. Insights about the contribution of the features to the stress detection performance can be obtained from Figure 1 and Figure 2 . Three of the best features (over 0.15 correlation) are frequency domain features. These features are high, low and very-low frequency components of the HRV signal (see Figure 1 ). When we examine the EDA features, peaks per 100 s feature are the most important and distinctive feature by far. Since the EDA signal is distorted under the influence of the stimuli, the number of peaks and valleys increases. Lastly, when the acceleration signal is investigated, the most discriminative feature is mean acceleration in the z -axis (see Figure 2 b). This could be due to the nature of hand and body gestures which are caused by stressed situations.

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Top-ranking features selected for the HRV signal.

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Top-ranking features selected for the EDA and ACC signals.

4.2. Relaxation Method Suggestion by Analyzing the Physical Activity-Based Context

Context is a broad term that could contain different types of information such as calendars, activity type, location and activity intensity. Physical activity intensity could be used to infer contextual information. In more restricted environments such as office, classrooms, public transportation and physical activity intensity could be low, whereas, in outdoor environments, physical activity intensity could increase. Therefore, an appropriate relaxation method will change according to the context of individuals.

For calculating physical activity intensity, we used the EDAExplorer tool [ 41 ]. The stillness metric is used for this purpose. It is the percentage of periods in which the person is still or motionless. Total acceleration must be less than a threshold (default is 0.1 [ 41 ]) for 95 percent of a minute in order for this minute to count as still [ 41 ]. Then, the ratio of still minutes in a session can be calculated. For the ratio of still minutes in a session, we labeled sessions below 20% as still, above 20% as active and suggested relaxation method accordingly (see Figure 3 ).

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The whole system diagram is depicted. When a high stress level is experienced, by analyzing the physical activity based context, the system suggests the most appropriate reduction method.

4.3. Description of the Data Collection Procedure

The proposed stress level monitoring mechanism, for real-life settings, was evaluated during an eight day Marie Skłodowska-Curie Innovative Training Network (ITN) training event in Istanbul, Turkey, for the AffecTech project. AffecTech is a program funded by Horizon 2020 (H2020) framework established by the European Commission. The AffecTech project is an international collaborative research network involving 15 PhD students (early stage researchers (ESR)) with the aim of developing low-cost effective wearable technologies for individuals who experience affective disorders (for example, depression, anxiety and bipolar disorder).

The eight-day training event included workshops, lectures and training with clearly defined tasks and activities to ensure that the ESR had developed the required skills, knowledge and values outline prior to the training event. At the end of the eight-day training, ESRs were required to deliver a presentation about their PhD work to two evaluators from the European Union where they received feedback about their progress (see Figure 4 for raw physiological signals at the start of the presentation). For studying the effects of emotion regulation on stress, yoga, guided mindfulness and mobile-based mindfulness, sessions were held by a certified instructor.

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Sample data belong to a presentation session. The increase in EDA, ST and IBI could be observed when the subject started the presentation.

During the training, physiological and questionnaire data were collected from the 16 ESR participants (9 men, mean age 28); 15 ESRs and one of the AffecTech project academics, all of whom gave informed consent to participate in the study. Participants were from different countries with diverse nationalities (two from Iran, two from Spain, two from Italy, one from Argentina, one from Pakistan, one from China, one from Switzerland, one from Belarus, one from France, one from England, one from Barbados, one from Turkey and one from Bulgaria). Due to the fault of one of the Empatica E4 devices, it was not possible to include data from one participant. The remaining 15 participants completed all stages of the study successfully.

During the eight days of training and presentations, psychophysiological data were collected from 16 participants during the training event from Empatica E4 smart band while they are awake. For studying the effects of emotion regulation on stress, yoga, guided mindfulness and mobile-based mindfulness sessions were held by a certified instructor. The timeline of the event is shown in Figure 5 .

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Time-line depicting eight days of the training event. Presentations, relaxations and lectures are highlighted.

4.3.1. Physiological Stress Data

The psychophysiological signal data were collected using the Empatica E4 smart band whilst participants were awake throughout the eight days of the AffecTech training. Physiological data included IBI, EDA, ACC (Accelerometer) and ST and stored in different csv files. In addition, 27.39% of the data are obtained from free times (free day and after training until subjects slept 5:00 p.m.–10:00 p.m.), 43.83% of the data comes from lectures in the training, 11.41% is the presentation session and relax sessions consist of 17.35% of the data. As mentioned previously, we randomly undersampled (most commonly applied method [ 55 ] ) the data to overcome the class imbalance problem. The participants’ blood pressure (BP) was also recorded using CE(0123) Harvard Medical Devices Ltd. automated sphygmomanometer prior to and after each stress reduction event (yoga and mindfulness), in order to demonstrate whether the participants stress levels were modified. On each occasion that the participants’ BP was recorded, the mean of three recordings was used as the final BP. A reduction in the participants’ blood pressure and/or pulse rate may be seen, which demonstrates a reduction in stress level.

4.3.2. Ethics

The procedure used in this study was approved by the Institutional Review Board for Research with Human Subjects of Boğaziçi University with the approval number 2018/16. Prior to data acquisition, each participant received a consent form describing the experimental procedure and its benefits and implications to both the society and the subject. The procedure was also explained verbally to the subject. All of the data are stored anonymously.

4.3.3. Questionnaire Self-Report Stress Data

A session-based self-report questionnaire comprised of six questions based on the Nasa Task Load Index (NASA-TLX) [ 57 ]. The frustration scale was specifically used to measure perceived stress levels [ 32 ]. We asked the following question to the participants for each session:

How irritated, stressed and annoyed versus content, relaxed and complacent did you feel during the task?

Questionnaires were completed daily (at the end of the day) and, after each presentation, lecture and stress reduction event (such as yoga and mindfulness).

4.3.4. Stress Management Scheme Using Yoga and Mindfulness

During the eight day training, it is assumed that the participants’ stress levels are likely to have increased day by day because they were required to give a presentation (perceived as a stressful event) reporting their PhD progress to the EU project evaluators at the end of the training.

Underpinned by James Gross’s Emotion Regulation model (see Figure 6 ) [ 4 ], we modified the situation to help the participants to reduce their thoughts of the end of the training presentation. To help participants manage their stress levels, we applied Yoga and mindfulness sessions on two separate days (day three and day four, respectively). These sessions lasted approximately 1 h and, throughout the sessions, participants wore an Empatica E4 smartband. In addition to the physiological signals coming from the Smartbands, participants’ blood pressure values were also recorded before and after the yoga and mindfulness sessions.

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Application of James Gross’s Emotion Regulation model [ 4 ] in the context of stress management.

5. Experimental Results and Discussion

5.1. statistical data analysis, 5.1.1. validation of different perceived stress levels by using the self-reports.

In order to validate that the participants experienced different perceived stress levels in different contexts (lecture, relaxation, presentation), we used the Frustration item (see Section 4.5) from the NASA-TLX [ 57 ]. The distribution of answers is demonstrated in Figure 7 . Our aim is to show that the perceived stress levels (obtained from self-report answers) differ in relaxation sessions considerably when compared to the presentation session (high stress). To this end, we applied the t -test (in R programming language) to the perceived stress self-report answers of yoga versus presentation, mindfulness versus presentation and pause (mobile mindfulness) versus presentation session pairs. The paired t -test is used to evaluate the separability of each session. The degree of freedom is 15. We applied the variance test to each session tuple; we could not identify equal variance in any of the session tuples. Thus, we selected the variance as unequal. We used 99.5% confidence intervals. The t -test results’ ( p -values and test statistics) are provided in Table 5 . For all tuples, the null hypothesis stating that the perceived stress of the relaxation method is not less than the presentation session is rejected. The perceived stress levels of participants for all meditation sessions are observed to be significantly lower than the presentation session (high stress).

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Visual representation of the frustration scores collected in different types of sessions.

T -test results for session tuple comparison of perceived stress levels using self-reports.

Session Tuple	-Test Statistic	-Value
Yoga—Presentation	−4.0027	< 0.005
Guided Mindfulness—Presentation	−5.4905	< 0.005
Mobile Mindfulness—Presentation	−4.2677	< 0.005

5.1.2. Before and After Physiological Measurements for Evaluating Performance of Yoga and Mindfulness with Blood Pressure

In this section, we compared the effect of stress management tools such as yoga and mindfulness on blood pressure. It is expected that blood pressure sensors will be part of unobtrusive wrist-worn wearable sensors soon. We plan to integrate a blood pressure (BP) module to our system when they are available. Therefore, by using the measurements of a medical-grade blood pressure monitor, we provided insights about how stress reaction affects BP. We further applied and tested the prominent emotion regulation model of James Gross by analyzing these measurements in the context of stress management. We measured the diastolic and systolic BP and pulse using a medical-grade blood pressure monitor before and after the yoga and mindfulness sessions. In order to ensure that the participants were relaxed and that an accurate BP was recorded, BP was measured three times with the mean as the recorded result. A one-sample t -test was applied to the difference between mean values. The results are shown in Table 6 .

The difference between the mean diastolic blood pressure, the mean systolic blood pressure and the mean pulse, before and after sessions of guided mindfulness and guided yoga. (* p < 0.05).

Activity	Systolic	Diastolic	Pulse
Guided Mindfulness	−1.31%	1.75% *	−5.75% *
Guided Yoga	−5.81% *	−1.93%	8.06% *

Mindfulness decreased the systolic BP, –1.13% (ns), increased diastolic BP, +1.75% ( p < 0.05) and decreased the pulse –5.75% ( p < 0.05). Medicine knows that systolic blood pressure (the top number or highest blood pressure when the heart is squeezing and pushing the blood around the body) is more important than diastolic blood pressure (the bottom number or lowest blood pressure between heartbeats) because it gives the best idea of the risk of having a stroke or heart attack. In this view, the significant reduction of systolic BP after mindfulness is an important result.

Moreover, the difference between systolic and diastolic BP is called pulse pressure. For example, 120 systolic minus 60 diastolic equals a pulse pressure of 60. It is also known that a pulse pressure greater than 60 can be a predictor of heart attacks or other cardiovascular diseases, while a low pulse pressure (less than 40) may indicate poor heart function. In our study, pulse pressure was lower after mindfulness (we had both a significant reduction in systolic BP and an increase in diastolic BP), but its value was higher than 40 (42.69 mean difference before the mindfulness and 40.48 mean difference after the mindfulness), suggesting that this result can also be considered clinically positive.

During yoga, there was a decrease in systolic BP by −5.81% ( p < 0.05), diastolic BP by −1.93% (ns) and increase in pulse +8.06% ( p < 0.05). Yoga appears to be more effective than mindfulness at decreasing systolic and diastolic blood pressure, although mindfulness seems to be more effective than yoga for decreasing the pulse due to the activity involved in yoga.

5.2. Physiological Stress Level Detection with Wearables by Using Context Labels as the Class Label

We tested our system by using the known context labels of sessions as the class label. We used Lecture (mild stress), Yoga and Mindfulness (relax) and Presentation in front of the board of juries (high stress) as class labels by examining perceived stress self-report answers in Figure 6 . We investigated the success of relaxation methods, different modalities and finding the presenter.

5.2.1. Effect of Different Physiological Signals on Stress Detection

We evaluated the effect of using the interbeat-interval, the skin conductance and the accelerometer signals separately and in a combined manner on two and three class classification performance. These classes are mild stress, high stress and relax states from mindfulness and yoga sessions. The results are shown in Table 7 , Table 8 and Table 9 . For the three-class classification problem, we achieved a maximum accuracy of 72% by using MLP on only HRV features and 86.61% with only accelerometer features using the Random Forest classifier and 85.36% accuracy combination of all features with LDA classifier (see Table 7 ). The difficulty in this classification task is a similar physiological reaction to relax and mild stress situations. However, since the main focus of our study is to discriminate high stress from other classes to offer relaxation techniques in this state, it did not affect our system performance. We also investigated high-mild stress and high stress-relax 2-class classification performance. For the discrimination of high and mild stress, HRV outperformed other signals with 98% accuracy using MLP (see Table 8 ). In the high stress-relax 2-class problem, only HRV features with RF achieved a maximum accuracy of 86%, whereas ACC features with MLP achieved a maximum of 94% accuracy. In this problem, the combination of all signals with RF achieved 92% accuracy which is the best among all classifiers (see Table 9 ). For all models, EDA did not perform well. This might be caused by the loose contact with EDA electrodes in the strap due to loosely worn smartbands.

Effect of different modalities and their combination on the system performance. Note that the number of classes is fixed at 3 (high stress, mild stress and relax).

Algorithm	Accuracy, %
Algorithm	HRV	EDA	ACC	Combined
MLP	72.14	36.61	74.29	82.68
RF	67.86	36.96	86.61	85.18
kNN	65.00	29.82	70.89	78.39
LDA	69.82	31.96	73.39	85.36
SVM	47.14	30.54	58.57	46.96

Effect of different modalities and their combination on the system performance. Note that the number of classes is fixed at 2 (high stress and mild stress).

Algorithm	Accuracy, %
Algorithm	HRV	EDA	ACC	Combined
MLP	98.00	60.00	64.00	98.00
RF	98.00	42.00	72.00	98.00
kNN	94.00	44.00	58.00	94.00
LDA	94.00	40.00	54.00	94.00
SVM	66.00	54.00	54.00	66.00

Effect of different modalities and their combination on the system performance. Note that the number of classes is fixed at 2 (high stress and relax).

Algorithm	Accuracy, %
Algorithm	HRV	EDA	ACC	Combined
MLP	82.00	66.00	96.00	90.00
RF	86.00	60.00	94.00	92.00
kNN	82.00	66.00	88.00	90.00
LDA	78.00	64.00	92.00	88.00
SVM	78.00	62.00	52.00	74.00

5.2.2. Effectiveness of Yoga, Mindfulness and Mobile Mindfulness (Pause)

We applied three different relaxation methods to manage stress levels of individuals. In order to measure the effectiveness of each method, we examined how easily these physiological signals in the relaxation sessions can be separated from high stress presentations. If it can be separated from high stress levels with higher classification performance, it could be inferred that they are more successful at reducing stress. As seen in Table 10 and Table 11 , mobile mindfulness has lower success in reducing stress levels. Yoga has the highest classification performance with both HR and EDA signals.

The classification accuracy of the relaxation sessions using stress management methods and stressful sessions using EDA.

Algorithm	Accuracy, %
Algorithm	Guided Mindfulness	Yoga	Mobile Mindfulness
MLP	65.71	78.57	75.00
RF	67.14	87.14	67.64
kNN	64.29	82.86	77.94
LDA	65.71	80.00	51.47
SVM	70.00	72.86	58.82

The classification accuracy of the relaxation sessions using stress management methods and stressful sessions using HRV.

Algorithm	Accuracy, %
Algorithm	Guided Mindfulness	Yoga	Mobile Mindfulness
MLP	90.00	97.50	93.94
RF	97.50	95.00	87.89
kNN	90.00	90.00	93.93
LDA	87.50	87.50	75.75
SVM	85.00	80.00	81.82

6. Conclusions

In this study, by using our automatic stress detection system with the use of Empatica-E4 smart-bands, we detected stress levels and suggested appropriate relaxation methods (i.e., traditional or mobile) when high stress levels are experienced. Our stress detection framework is unobtrusive, comfortable and suitable for use in daily life and our relaxation method suggestion system makes its decisions based on the physical activity-related context of a user. To test our system, we collected eight days of data from 16 individuals participating in an EU research project training event. Individuals were exposed to varied stressful and relaxation events (1) training and lectures (mild stress), (2) yoga, mindfulness and mobile mindfulness (PAUSE) (relax) and (3) were required to give a moderated presentation (high stress). The participants were from different countries with diverse cultures.

In addition, 1440 h of mobile data (12 h in a day) were collected during this eight-day event from each participant measuring their stress levels. Data were collected during the training sessions, relaxation events and the moderated presentation and during their free time for 12 h in a day, demonstrating that our study monitored daily life stress. EDA and HR signals were collected to detect physiological stress and a combination of different modalities increased stress detection, performance and provided the most discriminative features. We first applied James Gross ER model in the context of stress management and measured the blood pressure during the ER cycle. When the known context was used as the label for stress level detection system, we achieved 98% accuracy for 2-class and 85% accuracy for 3-class. Most of the studies in the literature only detect stress levels of individuals. The participants’ stress levels were managed with yoga, mindfulness and a mobile mindfulness application while monitoring their stress levels. We investigated the success of each stress management technique by the separability of physiological signals from high-stress sessions. We demonstrated that yoga and traditional mindfulness performed slightly better than the mobile mindfulness application. Furthermore, this study is not without limitations. In order to generalize the conclusions, more experiments based on larger sample groups should be conducted. As future work, we plan to develop personalized perceived stress models by using self-reports and test our system in the wild. Furthermore, attitudes in the psychological field constitute a topic of utmost relevance, which always play an instrumental role in the determination of human behavior [ 58 ]. We plan to design a new experiment which accounts for the attitudes of participants towards relaxation methods and their effects on the performance of stress recognition systems.

Acknowledgments

We would like to show our gratitude to the Affectech Project for providing us the opportunity for the data collection in the training event and funding the research.

Author Contributions

Y.S.C. is the main editor of this work and made major contributions in data collection, analysis and manuscript writing. H.I.-S. made valuable contributions in both data collection and manuscript writing. She was the yoga and mindfulness instructor in the event and contributed the related sections regarding traditional and mobile methods. She also led the blood pressure measurement efforts before and after relaxation methods. D.E. and N.C. contributed equally to this work in design, implementation, data analysis and writing the manuscript. J.F.-Á., C.R. and G.R. contributed the experiment design and provided valuable insights into both emotion regulation theory. They also contributed to the related sections in the manuscript. C.E. provided invaluable feedback and technical guidance to interpret the design and the detail of the field study. He also performed comprehensive critical editing to increase the overall quality of the manuscript. All authors have read and agreed to the published version of the manuscript.

This work has been supported by AffecTech: Personal Technologies for Affective Health, Innovative Training Network funded by the H2020 People Programme under Marie Skłodowska-Curie Grant Agreement No. 722022. This work is supported by the Turkish Directorate of Strategy and Budget under the TAM Project number DPT2007K120610.

Conflicts of Interest

The authors declare no conflict of interest.

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How to Relax in Stressful Situations: A Smart Stress Reduction System

Heather Iles-Smith

Niaz Chalabianloo

Claudia Repetto

1. Introduction

2. Background

2.2. Yoga and Mindfulness: As Tools for Emotion Regulation

2.2.2. Mindfulness

2.2.3. Mobile Mindfulness Inspired By Tai-Chi—Pause

3. Related Work

4. Methodology

4.1.1. EDA Preprocessing Artifact Detection and Removal Methods

4.1.2. EDA Feature Extraction Methods

Tonic Component Features

Phasic Component Features

4.1.3. Heart Activity Preprocessing (Artifact Detection and Removal) and Feature Extraction Methods

4.1.4. Accelerometer Feature Extraction Methods

4.1.5. Skin Temperature