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Assessing Anxiety Disorders Using Wearable Devices: Challenges and Future Directions

1,2,3,4,* and 1,*
1
Menrva Research Group, Schools of Mechatronic Systems Engineering and Engineering Science, Simon Fraser University, Surrey, BC V3T 0A3, Canada
2
School of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
3
Faculty of Medicine, University of British Columbia, Vancouver, BC V1Y 1T3, Canada
4
BC Children’s & Women’s Hospital, Vancouver, BC V6H 3N1, Canada
*
Authors to whom correspondence should be addressed.
Brain Sci. 2019, 9(3), 50; https://doi.org/10.3390/brainsci9030050
Received: 4 February 2019 / Revised: 14 February 2019 / Accepted: 26 February 2019 / Published: 1 March 2019
(This article belongs to the Collection Collection on Clinical Neuroscience)
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Abstract

Wearable devices (WD) are starting to increasingly be used for interventions to promote well-being by reducing anxiety disorders (AD). Electrocardiogram (ECG) signal is one of the most commonly used biosignals for assessing the cardiovascular system as it significantly reflects the activity of the autonomic nervous system during emotional changes. Little is known about the accuracy of using ECG features for detecting ADs. Moreover, during our literature review, a limited number of studies were found that involve ECG collection using WD for promoting mental well-being. Thus, for the sake of validating the reliability of ECG features for detecting anxiety in WD, we screened 1040 articles, and only 22 were considered for our study; specifically 6 on panic, 4 on post-traumatic stress, 4 on generalized anxiety, 3 on social, 3 on mixed, and 2 on obsessive-compulsive anxiety disorder articles. Most experimental studies had controversial results. Upon reviewing each of these papers, it became apparent that the use of ECG features for detecting different types of anxiety is controversial, and the use of ECG-WD is an emerging area of research, with limited evidence suggesting its reliability. Due to the clinical nature of most studies, it is difficult to determine the specific impact of ECG features on detecting ADs, suggesting the need for more robust studies following our proposed recommendations. View Full-Text
Keywords: digital medicine; anxiety; depression; mental well-being; flourishing; self-help with email support; biosignals; mental health promotion; wearable devices digital medicine; anxiety; depression; mental well-being; flourishing; self-help with email support; biosignals; mental health promotion; wearable devices
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Elgendi, M.; Menon, C. Assessing Anxiety Disorders Using Wearable Devices: Challenges and Future Directions. Brain Sci. 2019, 9, 50.

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