CuePD: An IoT approach for Enhancing Gait Rehabilitation in older adults through Personalised Music Cueing

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.