Wearable Devices for Gait Analysis in Intelligent Healthcare

Liu, Xin and Zhao, Chen and Zheng, Bin and Guo, Qinwei and Duan, Xiaoqin and Wulamu, Aziguli and Zhang, Dezheng (2021) Wearable Devices for Gait Analysis in Intelligent Healthcare. Frontiers in Computer Science, 3. ISSN 2624-9898

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Abstract

In this study, we review the role of wearable devices in tracking our daily locomotion. We discuss types of wearable devices that can be used, methods for gait analyses, and multiple healthcare-related applications aided by artificial intelligence. Impaired walking and locomotion are common resulting from injuries, degenerative pathologies, musculoskeletal disorders, and various neurological damages. Daily tracking and gait analysis are convenient and efficient approaches for monitoring human walking, where concreate and rich data can be obtained for examining our posture control mechanism during body movement and providing enhanced clinical pieces of evidence for diagnoses and treatments. Many sensors in wearable devices can help to record data of walking and running; spatiotemporal and kinematic variables can be further calculated in gait analysis. We report our previous works in gait analysis, discussing applications of wearable devices for detecting foot and ankle lesions, supporting surgeons in early diagnosis, and helping physicians with rehabilitation.

Item Type: Article
Subjects: STM Library > Computer Science
Depositing User: Managing Editor
Date Deposited: 26 Nov 2022 04:51
Last Modified: 07 May 2024 04:23
URI: http://open.journal4submit.com/id/eprint/290

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