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In clinical, the center of pressure (CoP) is commonly used for accessing the stability of a person&#x2019;s postural control, which is highly associated with various neurological diseases and movement disorders such as Alzheimer&#x2019;s disease, Parkinson&#x2019;s disease, chronic ankle instability. Such a disease usually has a long development or rehabilitation process which requires long-term CoP monitoring. The current CoP evaluation process does not meet the requirement, as it is often complicated and expensive through either the lab-based equipment or the clinical evaluation procedure. Different wearable sensor-based systems with less cost and restrictions have emerged, but their way of CoP calculation requires deliberate calibration of the positions of their sensors, which are not feasible in daily CoP monitoring. In this study, we developed a long-term CoP monitoring system in a smart-shoe form. First, a thin and flexible smart insole with optimal sensor locations was designed to be compact and energy sufficient for a whole-day usage. Then, a user-friendly app on the smartphone with a cloud-based data managing system was developed for applications in both clinical and home environments. Additionally, a simplified CoP estimation model was created without the need for calibration. Lastly, a machine learning-based human activity recognition method was incorporated to make the CoP detection process more automatic. Through a thorough validation test with the clinical level lab equipment, our system can generate the CoP measurements with high accuracy.

A Shoe-Integrated Sensor System for Long- Term Center of Pressure Evaluation