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智能设备和可穿戴技术在检测和监测精神健康状况及压力方面的应用:系统评价。

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

机构信息

Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney, Broadway, Sydney, NSW 2007, Australia.

School of Nursing and Midwifery, Western Sydney University, Penrith, NSW 2747, Australia.

出版信息

Sensors (Basel). 2021 May 16;21(10):3461. doi: 10.3390/s21103461.

DOI:10.3390/s21103461
PMID:34065620
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8156923/
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.

摘要

最近,用于加速检测和随后管理这些疾病的心理健康和压力监测设备的产量有所增加。本综述的目的是识别和批判性评估最新的用于识别抑郁、焦虑和压力的智能设备和可穿戴技术,以及与这些检测相关的生理过程。使用 MEDLINE、CINAHL、Cochrane Central 和 PsycINFO 数据库来识别使用智能设备和可穿戴技术来检测或监测焦虑、抑郁或压力的研究。评估压力和焦虑的纳入文章一致地使用心率变异性 (HRV) 参数来检测焦虑和压力,后者通过 HRV 和脑电图 (EEG) 一起检测效果更好。皮肤电活动在最近的研究中得到了广泛应用,对压力检测具有很高的准确性;然而,其可靠性值得怀疑。抑郁主要是使用特定的 EEG 特征来检测的;然而,目前市场上还没有使用 EEG 检测抑郁的设备。本系统综述强调,许多商业上可用的智能设备使用的平均心率在检测压力和焦虑方面不如心率变异性、皮肤电活动和可能的呼吸率准确。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d31d/8156923/2f4e73fab96d/sensors-21-03461-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d31d/8156923/2f4e73fab96d/sensors-21-03461-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d31d/8156923/2f4e73fab96d/sensors-21-03461-g001.jpg

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