Mental Health Monitoring Device

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 linked to their detection. The MEDLINE, CINAHL, Cochrane Central, and PsycINFO databases were used to identify studies which utilized 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.

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Published
2025-03-06
DOI
https://doi.org/10.1109/rait65068.2025.11089379
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Mental Health Monitoring Device

V. K. Sharma, Pratul Arvind, Jayendra Kumar, Aditya Singh et al.
ECG Monitoring and Analysis
article

Mental Health Monitoring Device

V. K. Sharma, Pratul Arvind, Jayendra Kumar, Aditya Singh, N. K. Bhattacharyya, Monika Bhardwaj
article en

Abstract

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 linked to their detection. The MEDLINE, CINAHL, Cochrane Central, and PsycINFO databases were used to identify studies which utilized 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.

National Society of Professional Engineers (US), National Institute of Technology Jamshedpur (IN), Maharaja Engineering College (IN)
Openalex Percentile: Top 70%
ECG Monitoring and Analysis
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