Assessing Anxiety Disorders Using Wearable Devices: Challenges and Future Directions

Resource type
Date created
2019-03-01
Authors/Contributors
Author: Menon, Carlo
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 usingWDfor 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.
Document
Published as
Elgendi, M.; Menon, C. Assessing Anxiety Disorders Using Wearable Devices: Challenges and Future Directions. Brain Sci. 2019, 9, 50. DOI: 10.3390/brainsci9030050
Publication title
Brain Sci
Document title
Assessing Anxiety Disorders Using Wearable Devices: Challenges and Future Directions
Date
2019
Volume
9
Issue
50
Publisher DOI
10.3390/brainsci9030050
Copyright statement
Copyright is held by the author(s).
Scholarly level
Peer reviewed?
No
Language
Member of collection
Attachment Size
brainsci-09-00050.pdf 1.55 MB