scholarly journals Model Construction of Using Physiological Signals to Detect Mental Health Status

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaoqian Liu
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Sliding Window ◽  
Physiological Signals ◽  
Health State ◽  
Detection Model ◽  
Physiological Signal ◽  
State Detection

Background. Mental health is a direct indicator of human mental activity, and it also affects all aspects of the human body. It plays a very important role in monitoring human mental health. Objectives. To design a mental health state detection model based on physiological signals to detect human mental health. Methods. For the detection of mental health, the sliding window method is used to divide the physiological signal dataset and the corresponding time into several segments and then calculate the physiological signal data in the sliding window for each physiological signal to form a sequence of characteristic values; according to the heart rate variability of the physiological signal, the heart rate variability (HRV) is extracted from the interval spectrum waveform: through the discrete trend analysis in statistics, the change characteristics of the ECG signal are analyzed, and the sequence statistical indicators of the physiological signal are calculated. With the help of a support vector machine used for the significant accuracy with less computation power, the physiological signals of the mental state are classified, and the discriminant function of the mental health state signals is normalized. A mental health state detection model is constructed according to the index system, the optimal solution of the model is obtained through the optimization function, and the mental health state detection is completed. Result. The detection error of the proposed model is less which improves the detection accuracy and is less time consuming. Conclusion. The detection model using physiological signals is proposed to evaluate the mental health status. As compared to the other detection models, its detection time is short and method error is always less than 2% which shows its accuracy and effectiveness.

scholarly journals Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3461
Author(s):  
Blake Anthony Hickey ◽  
Taryn Chalmers ◽  
Phillip Newton ◽  
Chin-Teng Lin ◽  
David Sibbritt ◽  
...  
Keyword(s):  
Mental Health ◽  
Systematic Review ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Electrodermal Activity ◽  
Smart Devices ◽  
Stress Detection ◽  
Wearable Technologies ◽  
Detection Of Stress ◽  
Anxiety Depression

Recently, there has been an increase in the production of devices to monitor mental health and stress as means for expediting detection, and subsequent management of these conditions. The objective of this review is to identify and critically appraise the most recent smart devices and wearable technologies used to identify depression, anxiety, and stress, and the physiological process(es) linked to their detection. The MEDLINE, CINAHL, Cochrane Central, and PsycINFO databases were used to identify studies which utilised smart devices and wearable technologies to detect or monitor anxiety, depression, or stress. The included articles that assessed stress and anxiety unanimously used heart rate variability (HRV) parameters for detection of anxiety and stress, with the latter better detected by HRV and electroencephalogram (EGG) together. Electrodermal activity was used in recent studies, with high accuracy for stress detection; however, with questionable reliability. Depression was found to be largely detected using specific EEG signatures; however, devices detecting depression using EEG are not currently available on the market. This systematic review highlights that average heart rate used by many commercially available smart devices is not as accurate in the detection of stress and anxiety compared with heart rate variability, electrodermal activity, and possibly respiratory rate.

scholarly journals Heart rate variability moderates the effects of COVID-19-related stress and family adversity on emotional problems in adolescents: Testing models of differential susceptibility and diathesis stress

2021 ◽  
pp. 1-12
Author(s):  
Jonas G. Miller ◽  
Rajpreet Chahal ◽  
Jaclyn S. Kirshenbaum ◽  
Tiffany C. Ho ◽  
Anthony J. Gifuni ◽  
...  
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Emotional Problems ◽  
Differential Susceptibility ◽  
Adolescent Mental Health ◽  
Family Adversity ◽  
Health Related ◽  
Mental Health Difficulties ◽  
Related Stress

Abstract The COVID-19 pandemic is a unique period of stress, uncertainty, and adversity that will have significant implications for adolescent mental health. Nevertheless, stress and adversity related to COVID-19 may be more consequential for some adolescents’ mental health than for others. We examined whether heart rate variability (HRV) indicated differential susceptibility to mental health difficulties associated with COVID-19 stress and COVID-19 family adversity. Approximately 4 years prior to the pandemic, we assessed resting HRV and HRV reactivity to a well-validated stress paradigm in 87 adolescents. During the pandemic, these adolescents (ages 13–19) reported on their health-related stress and concerns about COVID-19, family adversity related to COVID-19, and their recent emotional problems. The association between COVID-19 stress and emotional problems was significantly stronger for adolescents who previously exhibited higher resting HRV or higher HRV reactivity. For adolescents who exhibited lower resting HRV or HRV augmentation, COVID-19 stress was not associated with emotional problems. Conversely, lower resting HRV indicated vulnerability to the effect of COVID-19 family adversity on emotional problems. Different patterns of parasympathetic functioning may reflect differential susceptibility to the effects of COVID-19 stress versus vulnerability to the effects of COVID-19 family adversity on mental health during the pandemic.

scholarly journals Associations Between Heart Rate Variability Measured With a Wrist-Worn Sensor and Older Adults’ Physical Function: Observational Study

10.2196/13757 ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. e13757 ◽  
Author(s):  
Sarah Anne Graham ◽  
Dilip V Jeste ◽  
Ellen E Lee ◽  
Tsung-Chin Wu ◽  
Xin Tu ◽  
...  
Keyword(s):  
Older Adults ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Physical Health ◽  
Physical Function ◽  
Significant Proportion ◽  
Physical Health Status ◽  
Sf 36 ◽  
Composite Scores

Background Heart rate variability (HRV), or variation in beat-to-beat intervals of the heart, is a quantitative measure of autonomic regulation of the cardiovascular system. Low HRV derived from electrocardiogram (ECG) recordings is reported to be related to physical frailty in older adults. Recent advances in wearable technology offer opportunities to more easily integrate monitoring of HRV into regular clinical geriatric health assessments. However, signals obtained from ECG versus wearable photoplethysmography (PPG) devices are different, and a critical first step preceding their widespread use is to determine whether HRV metrics derived from PPG devices also relate to older adults’ physical function. Objective This study aimed to investigate associations between HRV measured with a wrist-worn PPG device, the Empatica E4 sensor, and validated clinical measures of both objective and self-reported physical function in a cohort of older adults living independently within a continuing care senior housing community. Our primary hypothesis was that lower HRV would be associated with lower physical function. In addition, we expected that HRV would explain a significant proportion of variance in measures of physical health status. Methods We evaluated 77 participants from an ongoing study of older adults aged between 65 and 95 years. The assessments encompassed a thorough examination of domains typically included in a geriatric health evaluation. We collected HRV data with the Empatica E4 device and examined bivariate correlations between HRV quantified with the triangular index (HRV TI) and 3 widely used and validated measures of physical functioning—the Short Physical Performance Battery (SPPB), Timed Up and Go (TUG), and Medical Outcomes Study Short Form 36 (SF-36) physical composite scores. We further investigated the additional predictive power of HRV TI on physical health status, as characterized by SF-36 physical composite scores and Cumulative Illness Rating Scale for Geriatrics (CIRS-G) scores, using generalized estimating equation regression analyses with backward elimination. Results We observed significant associations of HRV TI with SPPB (n=52; Spearman ρ=0.41; P=.003), TUG (n=51; ρ=−0.40; P=.004), SF-36 physical composite scores (n=49; ρ=0.37; P=.009), and CIRS-G scores (n=52, ρ=−0.43; P=.001). In addition, the HRV TI explained a significant proportion of variance in SF-36 physical composite scores (R2=0.28 vs 0.11 without HRV) and CIRS-G scores (R2=0.33 vs 0.17 without HRV). Conclusions The HRV TI measured with a relatively novel wrist-worn PPG device was related to both objective (SPPB and TUG) and self-reported (SF-36 physical composite) measures of physical function. In addition, the HRV TI explained additional variance in self-reported physical function and cumulative illness severity beyond traditionally measured aspects of physical health. Future steps include longitudinal tracking of changes in both HRV and physical function, which will add important insights regarding the predictive value of HRV as a biomarker of physical health in older adults.

scholarly journals Heart Rate Variability Moderates the Link Between COVID-19 Stress and Emotional Problems in Adolescents: Evidence for Differential Susceptibility

2020 ◽  
Author(s):  
Jonas G. Miller ◽  
Rajpreet Chahal ◽  
Jaclyn Schwartz Kirshenbaum ◽  
Tiffany C. Ho ◽  
Anthony J. Gifuni ◽  
...  
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Emotional Problems ◽  
Differential Susceptibility ◽  
Adolescent Mental Health ◽  
Health Related ◽  
Mental Health Difficulties ◽  
Related Stress

The COVID-19 pandemic is a unique period of stress and uncertainty that will have significant implications for adolescent mental health. Nevertheless, stress about COVID-19 may be more consequential for some adolescents’ mental health than for others. We examined whether heart rate variability (HRV) indicated differential susceptibility to mental health difficulties associated with COVID-19 stress. Approximately four years prior to the pandemic, we assessed resting HRV and HRV reactivity to a well-validated stress paradigm in 87 adolescents. During the pandemic, these adolescents (ages 13-19) reported on their health-related stress and concerns about COVID-19 and their recent emotional problems. The association between COVID-19 stress and emotional problems was significantly stronger for adolescents who previously exhibited higher resting HRV or higher HRV reactivity. For adolescents who exhibited lower resting HRV or lower HRV reactivity, COVID-19 stress was not associated with emotional problems. Thus, parasympathetic functioning may reflect differential susceptibility to the effects of COVID-19 stress on mental health during the pandemic.

Resonance breathing is associated with improvements in depression and anxiety symptoms during heart rate variability biofeedback sessions

2021 ◽  
Author(s):  
Adam Khan Pettitt ◽  
Benjamin W Nelson ◽  
Richard Gevirtz ◽  
Paul Lehrer ◽  
Kristian Ranta ◽  
...  
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Resonance Frequency ◽  
Treatment Protocol ◽  
Anxiety Symptoms ◽  
Adjunctive Treatment ◽  
Depression And Anxiety ◽  
Heart Rate Variability Biofeedback ◽  
Item Scale

Heart rate variability (HRV) appears to be a transdiagnostic biomarker for health and disease. Although initial studies using HRV biofeedback (HRVB) to regulate HRV as a potential adjunctive treatment to gold-standard interventions seem promising, more research is needed to determine which aspects of HRVB training provide the most clinical benefits to those suffering from mental health symptoms. In the current study, we sought to investigate whether time spent in resonance, between-person differences in resonance frequency, and/or within-person resonance frequency trajectory across repeated HRVB sessions were related to changes in depression and/or anxiety symptoms during a 12-week digital mental health intervention that contains HRVB as part of the treatment protocol. We used a retrospective cohort study to examine these associations among 387 participants in the Meru Health Program. For depression, we found that average resonance time per HRVB session, but not total time in resonance, was significantly associated with decreased depression as measured by the Patient Health Questionnaire 9-item scale (PHQ-9) across treatment (b=-0.38, 95% CI [-0.76,-0.01], t(377)=-1.99, p=.047). For anxiety symptoms as measured by the Generalized Anxiety Disorder 7-item scale (GAD-7), we found neither association significant. Within-person effects were significant for both depression and anxiety, with steeper slopes of time spent in resonance significantly related to reductions in PHQ-9 and GAD-7 symptoms, respectively. Between-person effects were not significant for either depression or anxiety. Our results demonstrate that improvements in resonance efficiency over time in treatment, independent of how each participant starts, are related to reductions in depression and anxiety symptoms.

scholarly journals Mental health status of refugee children

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
N Lemonjava ◽  
K Antia ◽  
M Lobjanidze ◽  
T Lobjanidze
Keyword(s):  
Mental Health ◽  
Health Status ◽  
Psychological Health ◽  
Psychological Trauma ◽  
Mental Health Status ◽  
Stress Factors ◽  
Refugee Children ◽  
Health State ◽  
Post Traumatic Stress ◽  
Host Countries

Abstract Background A number of refugees and asylum seekers have increased dramatically in recent years. More than 250 million people worldwide are considered as refugees (United Nations High Commission for Refugees, 2018), among whom more than 50% are children. General health and especially psychological health of the refugee and asylum seeking children are an emerging, however, not well explored issues. In this study, we aimed to review the literature on the psychological health of refugee children. Methods We performed a literature search and descriptive analysis of studies published until July 2019, through MEDLINE and Science Direct databases. We identified literature on psychological health state of refugee and asylum seeking children. We analysed results of 16 studies. Results The study found that refugee children are facing severe psychological health issues, such as Post-traumatic stress disorder (PTSD), depression, anxiety, sleep disorders, behavioural problems. We identified 3 phases of psychological trauma and stress among refugee children: stress due to conflict in their home countries, stress during migration, and upon the arrival to host country. Our analysis reviled integration difficulties such as racism and bulling as important stress factors for the refugee children. Studies found that prevalence of PTSD is more than 54% among refugee children residing in Norway, significantly higher than in reference population. The studies identified the need of regular mental health assessment and preventive care, psychological counselling services for the refugee children. All included studies showed significantly higher stress among refugee children when compared to local children in host countries. Conclusions Rehabilitation services and follow-up supportive programs should be implemented to improve the mental health status of refugee children; these interventions will also contribute to their better integration. Key messages Screening and regular monitoring provided by host countries healthcare system is crucial to identify high risk children. More research is needed to better investigate the psychological health state and needs of refugee children.

scholarly journals Evaluating physiological signal salience for estimating metabolic energy cost from wearable sensors

2019 ◽  
Vol 126 (3) ◽  
pp. 717-729 ◽  
Author(s):  
Kimberly A. Ingraham ◽  
Daniel P. Ferris ◽  
C. David Remy
Keyword(s):  
Heart Rate ◽  
Steady State ◽  
Indirect Calorimetry ◽  
Energy Cost ◽  
Electrodermal Activity ◽  
Wearable Sensors ◽  
Metabolic Energy ◽  
Physiological Signals ◽  
Physiological Signal ◽  
Signal Salience

Body-in-the-loop optimization algorithms have the capability to automatically tune the parameters of robotic prostheses and exoskeletons to minimize the metabolic energy expenditure of the user. However, current body-in-the-loop algorithms rely on indirect calorimetry to obtain measurements of energy cost, which are noisy, sparsely sampled, time-delayed, and require wearing a respiratory mask. To improve these algorithms, the goal of this work is to predict a user’s steady-state energy cost quickly and accurately using physiological signals obtained from portable, wearable sensors. In this paper, we quantified physiological signal salience to discover which signals, or groups of signals, have the best predictive capability when estimating metabolic energy cost. We collected data from 10 healthy individuals performing 6 activities (walking, incline walking, backward walking, running, cycling, and stair climbing) at various speeds or intensities. Subjects wore a suite of physiological sensors that measured breath frequency and volume, limb accelerations, lower limb EMG, heart rate, electrodermal activity, skin temperature, and oxygen saturation; indirect calorimetry was used to establish the ‘ground truth’ energy cost for each activity. Evaluating Pearson’s correlation coefficients and single and multiple linear regression models with cross validation (leave-one- subject-out and leave-one- task-out), we found that 1) filtering the accelerations and EMG signals improved their predictive power, 2) global signals (e.g., heart rate, electrodermal activity) were more sensitive to unknown subjects than tasks, while local signals (e.g., accelerations) were more sensitive to unknown tasks than subjects, and 3) good predictive performance was obtained combining a small number of signals (4–5) from multiple sensor modalities. NEW & NOTEWORTHY In this paper, we systematically compare a large set of physiological signals collected from portable sensors and determine which sensor signals contain the most salient information for predicting steady-state metabolic energy cost, robust to unknown subjects or tasks. This information, together with the comprehensive data set that is published in conjunction with this paper, will enable researchers and clinicians across many fields to develop novel algorithms to predict energy cost from wearable sensors.

Investigating the Effect of Mindfulness Training on Heart Rate Variability in Mental Health Outpatients: A Pilot Study

2014 ◽  
Vol 31 (3) ◽  
pp. 175-188 ◽  
Author(s):  
Alexis Wheeler ◽  
Linley Denson ◽  
Chris Neil ◽  
Graeme Tucker ◽  
Maura Kenny ◽  
...  
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Pilot Study ◽  
Short Form ◽  
Depression Scale ◽  
Cardiac Risk ◽  
Significant Treatment ◽  
Electrocardiographic Monitoring ◽  
Axis I

Depression is associated with increased cardiac morbidity and mortality in people with and without cardiac risk factors, and this relationship is, in part, mediated by heart rate variability (HRV). Increased heart rate and reduced HRV are common in depressed patients, which may explain their higher cardiac risk. This pilot study investigated whether mindfulness-based cognitive therapy (MBCT) promoted objective changes in (1) HRV, and (2) depressive symptoms and quality of life, in mental health outpatients. Twenty-seven adults meeting criteria for DSM-IV Axis I disorders completed an 8-week MBCT program. Data were collected on three occasions, 8 weeks apart; twice before and once after MBCT. Participants completed the Short Form-36 and the Center for Epidemiological Studies Depression Scale (CES-D) at each test period. Heart rate and HRV were measured during electrocardiographic monitoring before and after a cognitive stressor. At baseline, 78% of participants met criteria for depression (CES-D ≥16). Multivariate analyses revealed a significant treatment effect for SF-36 physical summary score and depression (as a dichotomous variable), but not for HRV. This pilot study highlights the immediate psychological and health benefits of MBCT. Low power may have influenced the lack of a finding of an association between HRV and MBCT. However, the feasibility of the study design has been established, and supports the need for larger and longer-term studies of the potential physiological benefits of MBCT for cardiac health.

scholarly journals Junior doctors in their first year: mental health, quality of life, burnout and heart rate variability

2013 ◽  
Vol 3 (2) ◽  
pp. 136-143 ◽  
Author(s):  
Marcus A. Henning ◽  
John Sollers ◽  
Joanna M. Strom ◽  
Andrew G. Hill ◽  
Mataroria P. Lyndon ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
First Year ◽  
Junior Doctors ◽  
Health Quality ◽  
Health Quality Of Life
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