survey

A Critical Review of Multimodal-multisensor Analytics for Anxiety Assessment

Authors:

Hashini Senaratne,

Glenn MelvinAuthors Info & Claims

ACM Transactions on Computing for Healthcare, Volume 3, Issue 4

Article No.: 46, Pages 1 - 42

https://doi.org/10.1145/3556980

Published: 03 November 2022 Publication History

Abstract

Recently, interest has grown in the assessment of anxiety that leverages human physiological and behavioral data to address the drawbacks of current subjective clinical assessments. Complex experiences of anxiety vary on multiple characteristics, including triggers, responses, duration and severity, and impact differently on the risk of anxiety disorders. This article reviews the past decade of studies that objectively analyzed various anxiety characteristics related to five common anxiety disorders in adults utilizing features of cardiac, electrodermal, blood pressure, respiratory, vocal, posture, movement, and eye metrics. Its originality lies in the synthesis and interpretation of consistently discovered heterogeneous predictors of anxiety and multimodal-multisensor analytics based on them. We reveal that few anxiety characteristics have been evaluated using multimodal-multisensor metrics, and many of the identified predictive features are confounded. As such, objective anxiety assessments are not yet complete or precise. That said, few multimodal-multisensor systems evaluated indicate an approximately 11.73% performance gain compared to unimodal systems, highlighting a promising powerful tool. We suggest six high-priority future directions to address the current gaps and limitations in infrastructure, basic knowledge, and application areas. Action in these directions will expedite the discovery of rich, accurate, continuous, and objective assessments and their use in impactful end-user applications.

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A Critical Review of Multimodal-multisensor Analytics for Anxiety Assessment

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cover image ACM Transactions on Computing for Healthcare

ACM Transactions on Computing for Healthcare Volume 3, Issue 4

October 2022

331 pages

EISSN:2637-8051

DOI:10.1145/3544003

Editors:
Insup Lee
University of Pennsylvania, USA
,
John A. Stankovic
University of Virginia, USA

Issue’s Table of Contents

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Publication History

Published: 03 November 2022

Online AM: 17 August 2022

Accepted: 07 August 2022

Revised: 06 July 2022

Received: 18 July 2021

Published in HEALTH Volume 3, Issue 4

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https://doi.org/10.1016/j.ijmedinf.2024.105682
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