CuePD: An IoT approach for Enhancing Gait Rehabilitation in older adults through Personalised Music Cueing
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Authors
Walker, Richard
Issue Date
2024
Type
Article
Language
en
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Abstract
Falls in people with Parkinson's disease (PwPD) underscore the need for precise sensing tools to robustly assess gait and deliver tailored rehabilitation. Using wearable inertial measurement units (IMUs) offers a practical alternative to assess gait and intervene in any location. This study develops a robust and innovative smartphone application/app that uses embedded IMU for real-time gait sensing to facilitate personalised cueing for targeted rehabilitation to reduce falls. Here, older adults had their CuePD based gait validated against a reference standard and were then exposed to different but personalised cueing modalities to target a 10.0% increase on cadence. CuePD increased cadence by 8.3% and showed robust agreement with the reference before and after cueing as evidenced by strong Pearson correlation coefficients (≥0.843) and intraclass correlation coefficients (≥0.845) across clinically relevant temporal gait characteristics (e.g., step time). Gait sensing via a smartphone is robust and CuePD indicates the feasibility of a scalable and personalised approach for targeted gait rehabilitation. Future research will extend to PwPD.
Description
Citation
Wall, C., Young, F., McMeekin, P. et al. CuePD: An IoT approach for Enhancing Gait Rehabilitation in older adults through Personalised Music Cueing. IEEE Sensors Letter; Early Access: 1-4.
Publisher
IEEE Sensors Letters
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PubMed ID
ISSN
2475-1472