Towards Accurate and Scalable Mental Health Screening Technologies for Young Children

被引：0

作者：

Kalanadhabhatta, Manasa ^{[1
]}

Ganesan, Deepak ^{[1
]}

Rahman, Tauhidur ^{[2
]}

机构：

[1] Univ Massachusetts Amherst, Amherst, MA 01003 USA

[2] Univ Calif San Diego, San Diego, CA USA

来源：

ADJUNCT PROCEEDINGS OF THE 2023 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING & THE 2023 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTING, UBICOMP/ISWC 2023 ADJUNCT | 2023年

关键词：

mental health; behavioral disorders; diagnostic assessments; brain sensing; wearable computing; mobile health; ATTENTION-DEFICIT/HYPERACTIVITY DISORDER; PARENT;

D O I：

10.1145/3594739.3610763

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Mental, emotional, and behavioral disorders are highly prevalent in preschool-aged children and can significantly affect their social-emotional development and adaptive functioning. However, identifying signs of problematic behavior at this age is extremely challenging due to several structural and phenomenological barriers. This work leverages mobile and wearable devices to build accurate, usable, and scalable assessment tools that can be deployed in home settings to screen for common disorders in young children. It describes the development of novel screening algorithms that utilize behavioral and neurophysiological signals recorded during brief, naturalistic tasks, and presents stakeholder perspectives toward the usability and clinical utility of such screening tools.

引用

页码：225 / 229

页数：5

共 43 条

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