Physiological monitoring of stress and major depression: A review of the current monitoring techniques and considerations for the future

Ahmed, Tashfia; Qassem, Meha; Kyriacou, P. A.

doi:10.1016/j.bspc.2022.103591

Cited by 13 publications

(7 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, Pedrelli et al [43] showed across 31 participants that EDA is a predictive factor of depression severity. These findings reflect that of previous research investigating EDA and depression in laboratory-based studies [44] , [45] , [46] . However, to our knowledge, no study has applied a wearable EDA device to monitor stress in remitted depression in everyday life.…”

Section: Introductionsupporting

confidence: 90%

Examining Stress and Residual Symptoms in Remitted and Partially Remitted Depression Using a Wearable Electrodermal Activity Device: A Pilot Study

Whiston

Igou

Fortune

et al. 2023

IEEE J. Transl. Eng. Health Med.

View full text Add to dashboard Cite

Objective: Consistent evidence suggests residual symptoms and stress are the most reliable predictors of relapse in remitted depression. Prevailing methodologies often do not enable continuous real-time sampling of stress. Thus, little is known about day-to-day interactions between residual symptoms and stress in remitted depression. In preparation for a full-scale trial, this study aimed to pilot a wrist-worn wearable electrodermal activity monitor: ADI (Analog Devices, Inc.) Study Watch for assessing interactions between physiological stress and residual depressive symptoms following depression remission. Methods: 13 individuals remitted from major depression completed baseline, daily diary, and post-daily diary assessments. Self-reported stress and residual symptoms were measured at baseline and post-daily diary. Diary assessments required participants to wear ADI's Study Watch during waking hours and complete self-report questionnaires every evening over one week. Results: Sleep problems, fatigue, energy loss, and agitation were the most frequently reported residual symptoms. Average skin conductance responses (SCRs) were 16.09 per-hour, with an average of 11.30 hours of wear time per-day. Increased residual symptoms were associated with enhanced self-reported stress on the same day. Increased SCRs on one day predicted increased residual symptoms on the next day. Conclusion: This study showed a wearable electrodermal activity device can be recommended for examining stress as a predictor of remitted depression. This study also provides preliminary work on relationships between residual symptoms and stress in remitted depression. Importantly, significant findings from the small sample of this pilot are preliminary with an aim to follow up with a 3-week full-scale study to draw conclusions about psychological processes explored.

show abstract

Section: Introductionsupporting

confidence: 90%

Examining Stress and Residual Symptoms in Remitted and Partially Remitted Depression Using a Wearable Electrodermal Activity Device: A Pilot Study

Whiston

Igou

Fortune

et al. 2023

IEEE J. Transl. Eng. Health Med.

View full text Add to dashboard Cite

show abstract

“…To advance in the field of mental health, it is crucial to establish reliable tools that allow to objectively assess the patient’s affectability and the effectiveness of applied interventions. The measurement of electrophysiological variables provides information about the functioning of the autonomic nervous system (ANS) and permits estimating the stress level non-invasively, being an extended quantitative approach for this purpose ( Ahmed et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Assessing effectiveness of heart rate variability biofeedback to mitigate mental health symptoms: a pilot study

Ribeiro

Sangrà²,

Pagès

et al. 2023

Front. Physiol.

View full text Add to dashboard Cite

Introduction: The increasing burden on mental health has become a worldwide concern especially due to its substantial negative social and economic impact. The implementation of prevention actions and psychological interventions is crucial to mitigate these consequences, and evidence supporting its effectiveness would facilitate a more assertive response. Heart rate variability biofeedback (HRV-BF) has been proposed as a potential intervention to improve mental wellbeing through mechanisms in autonomic functioning. The aim of this study is to propose and evaluate the validity of an objective procedure to assess the effectiveness of a HRV-BF protocol in mitigating mental health symptoms in a sample of frontline HCWs (healthcare workers) who worked in the COVID-19 pandemic.Methods: A prospective experimental study applying a HRV-BF protocol was conducted with 21 frontline healthcare workers in 5 weekly sessions. For PRE–POST intervention comparisons, two different approaches were used to evaluate mental health status: applying (a) gold-standard psychometric questionnaires and (b) electrophysiological multiparametric models for chronic and acute stress assessment.Results: After HRV-BF intervention, psychometric questionnaires showed a reduction in mental health symptoms and stress perception. The electrophysiological multiparametric also showed a reduction in chronic stress levels, while the acute stress levels were similar in PRE and POST conditions. A significant reduction in respiratory rate and an increase in some heart rate variability parameters, such as SDNN, LFn, and LF/HF ratio, were also observed after intervention.Conclusion: Our findings suggest that a 5-session HRV-BF protocol is an effective intervention for reducing stress and other mental health symptoms among frontline HCWs who worked during the COVID-19 pandemic. The electrophysiological multiparametric models provide relevant information about the current mental health state, being useful for objectively evaluating the effectiveness of stress-reducing interventions. Further research could replicate the proposed procedure to confirm its feasibility for different samples and specific interventions.

show abstract

“…A new method for evaluating stressed and depressed people’s psychophysiology has emerged in recent years because of the measurement and objectification of stress [ 12 ]. Researchers collected data from a diverse range of users in around 100 nations using a well-known meditation app, including heart rate variability (HRV) and heart rate (HR), besides the self-assessment of stress [ 13 ]. Those data were recorded using a mobile camera as a standalone or as a voluntary pair before and after the assessments.…”

Section: Introductionmentioning

confidence: 99%

An Innovative Random-Forest-Based Model to Assess the Health Impacts of Regular Commuting Using Non-Invasive Wearable Sensors

Sharif

Tamang

et al. 2023

Sensors

View full text Add to dashboard Cite

Regular commutes to work can cause chronic stress, which in turn can cause a physical and emotional reaction. The recognition of mental stress in its earliest stages is very necessary for effective clinical treatment. This study investigated the impact of commuting on human health based on qualitative and quantitative measures. The quantitative measures included electroencephalography (EEG) and blood pressure (BP), as well as weather temperature, while qualitative measures were established from the PANAS questionnaire, and included age, height, medication, alcohol status, weight, and smoking status. This study recruited 45 (n) healthy adults, including 18 female and 27 male participants. The modes of commute were bus (n = 8), driving (n = 6), cycling (n = 7), train (n = 9), tube (n = 13), and both bus and train (n = 2). The participants wore non-invasive wearable biosensor technology to measure EEG and blood pressure during their morning commute for 5 days in a row. A correlation analysis was applied to find the significant features associated with stress, as measured by a reduction in positive ratings in the PANAS. This study created a prediction model using random forest, support vector machine, naive Bayes, and K-nearest neighbor. The research results show that blood pressure and EEG beta waves were significantly increased, and the positive PANAS rating decreased from 34.73 to 28.60. The experiments revealed that measured systolic blood pressure was higher post commute than before the commute. For EEG waves, the model shows that the EEG beta low power exceeded alpha low power after the commute. Having a fusion of several modified decision trees within the random forest helped increase the performance of the developed model remarkably. Significant promising results were achieved using random forest with an accuracy of 91%, while K-nearest neighbor, support vector machine, and naive Bayes performed with an accuracy of 80%, 80%, and 73%, respectively.

show abstract

Physiological monitoring of stress and major depression: A review of the current monitoring techniques and considerations for the future

Cited by 13 publications

References 65 publications

Examining Stress and Residual Symptoms in Remitted and Partially Remitted Depression Using a Wearable Electrodermal Activity Device: A Pilot Study

Examining Stress and Residual Symptoms in Remitted and Partially Remitted Depression Using a Wearable Electrodermal Activity Device: A Pilot Study

Assessing effectiveness of heart rate variability biofeedback to mitigate mental health symptoms: a pilot study

An Innovative Random-Forest-Based Model to Assess the Health Impacts of Regular Commuting Using Non-Invasive Wearable Sensors

Contact Info

Product

Resources

About