Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review
Hickey, BA
Chalmers, T
Newton, P
Lin, C-T
Sibbritt, D
McLachlan, CS
Clifton-Bligh, R
Morley, J
Lal, S
- Publisher:
- MDPI
- Publication Type:
- Journal Article
- Citation:
- Sensors, 2021, 21, (10), pp. 1-17
- Issue Date:
- 2021-05-16
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Hickey, BA | |
dc.contributor.author | Chalmers, T | |
dc.contributor.author | Newton, P | |
dc.contributor.author | Lin, C-T | |
dc.contributor.author |
Sibbritt, D https://orcid.org/0000-0003-3561-9447 |
|
dc.contributor.author | McLachlan, CS | |
dc.contributor.author | Clifton-Bligh, R | |
dc.contributor.author | Morley, J | |
dc.contributor.author |
Lal, S https://orcid.org/0000-0002-0911-0850 |
|
dc.date.accessioned | 2021-12-01T05:37:29Z | |
dc.date.available | 2021-05-11 | |
dc.date.available | 2021-12-01T05:37:29Z | |
dc.date.issued | 2021-05-16 | |
dc.identifier.citation | Sensors, 2021, 21, (10), pp. 1-17 | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/10453/151988 | |
dc.description.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(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 | |
dc.format | Electronic | |
dc.language | eng | |
dc.publisher | MDPI | |
dc.relation.ispartof | Sensors | |
dc.relation.isbasedon | 10.3390/s21103461 | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | 0301 Analytical Chemistry, 0502 Environmental Science and Management, 0602 Ecology, 0805 Distributed Computing, 0906 Electrical and Electronic Engineering | |
dc.subject.classification | Analytical Chemistry | |
dc.subject.mesh | Monitoring, Physiologic | |
dc.subject.mesh | Reproducibility of Results | |
dc.subject.mesh | Mental Health | |
dc.subject.mesh | Heart Rate | |
dc.subject.mesh | Wearable Electronic Devices | |
dc.subject.mesh | Heart Rate | |
dc.subject.mesh | Mental Health | |
dc.subject.mesh | Monitoring, Physiologic | |
dc.subject.mesh | Reproducibility of Results | |
dc.subject.mesh | Wearable Electronic Devices | |
dc.title | Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review | |
dc.type | Journal Article | |
utslib.citation.volume | 21 | |
utslib.location.activity | Switzerland | |
utslib.for | 0301 Analytical Chemistry | |
utslib.for | 0502 Environmental Science and Management | |
utslib.for | 0602 Ecology | |
utslib.for | 0805 Distributed Computing | |
utslib.for | 0906 Electrical and Electronic Engineering | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Health | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Science | |
pubs.organisational-group | /University of Technology Sydney/Strength - CHSP - Health Services and Practice | |
pubs.organisational-group | /University of Technology Sydney/Strength - CHT - Health Technologies | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Science/School of Life Sciences | |
pubs.organisational-group | /University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Health/Public Health | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science | |
pubs.organisational-group | /University of Technology Sydney/Centre for Health Technologies (CHT) | |
utslib.copyright.status | open_access | * |
pubs.consider-herdc | false | |
dc.date.updated | 2021-12-01T05:37:28Z | |
pubs.issue | 10 | |
pubs.publication-status | Published | |
pubs.volume | 21 | |
utslib.citation.issue | 10 |
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(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
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