Remote Extended Reality With Markerless Motion Tracking for Sitting Posture Training

Dynamic postural control during sitting is essential for functional mobility and daily activities. Extended reality (XR) presents a promising solution for posture training in addressing conventional training limitations related to patient accessibility and ecological validity. We developed a remote XR rehabilitation system with markerless motion tracking for sitting posture training. Forty-two healthy subjects participated in this proof-of-concept pilot study. Each subject completed 24 rounds of multi-directional reach tasks using the system and 24 rounds without it. Motion data were collected via online meetings using built-in camera in the user's laptop. Functional reach test scores were analyzed to assess the impact of the system on motor performance. Four standard questionnaires were used to assess the effects of this system on presence, simulator sickness, engagement, and enjoyment. Our results indicate that the remote XR training system significantly improved functional reach performance and proved highly effective for telerehabilitation. XR interaction also enhanced training engagement and enjoyment. By bridging the spatial gap between patients and therapists, this system enables personalized and engaging home-based intervention. Additionally, it facilitates more natural movements by eliminating body marker constraints and laboratory limitations. This study should serve as a stepping stone to advancing novel remote XR rehabilitation systems.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-09-13
DOI
https://doi.org/10.1109/lra.2024.3460412
Citations
4
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
1.49

Funders

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article

Remote Extended Reality With Markerless Motion Tracking for Sitting Posture Training

Xupeng Ai, Sunil Kumar Agrawal
4 citations
IEEE Robotics and Automation Letters
Virtual Reality Applications and Impacts
1.49
article

Remote Extended Reality With Markerless Motion Tracking for Sitting Posture Training

Xupeng Ai, Sunil Kumar Agrawal
article en
4 citations

Abstract

Dynamic postural control during sitting is essential for functional mobility and daily activities. Extended reality (XR) presents a promising solution for posture training in addressing conventional training limitations related to patient accessibility and ecological validity. We developed a remote XR rehabilitation system with markerless motion tracking for sitting posture training. Forty-two healthy subjects participated in this proof-of-concept pilot study. Each subject completed 24 rounds of multi-directional reach tasks using the system and 24 rounds without it. Motion data were collected via online meetings using built-in camera in the user's laptop. Functional reach test scores were analyzed to assess the impact of the system on motor performance. Four standard questionnaires were used to assess the effects of this system on presence, simulator sickness, engagement, and enjoyment. Our results indicate that the remote XR training system significantly improved functional reach performance and proved highly effective for telerehabilitation. XR interaction also enhanced training engagement and enjoyment. By bridging the spatial gap between patients and therapists, this system enables personalized and engaging home-based intervention. Additionally, it facilitates more natural movements by eliminating body marker constraints and laboratory limitations. This study should serve as a stepping stone to advancing novel remote XR rehabilitation systems.

IEEE Robotics and Automation LettersVol. 9(11)
Columbia University (US)
National Institutes of Health
Openalex Percentile: Top 17%
Virtual Reality Applications and Impacts
1.49
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Remote Extended Reality With Markerless Motion Tracking for Sitting Posture Training — Xupeng Ai, Sunil Kumar Agrawal · IEEE Robotics and Automation Letters (2024) | TGRS Research Map | TGRS