As the aging population continues to grow, the demand for accessible cost-effective solutions for rehabilitation and mobility monitoring becomes increasingly urgent. The work presents a new protocol using easy-to-wear sensors that will enable continuous real-time tracking of ankle mobility and muscle performance. A wearable system is designed as based on Inertial Measurement Units (IMU) for real-time ankle mobility tracking, aiming to provide an affordable alternative to traditional high-cost motion analysis systems. The system’s performance is compared to the gold-standard Motion Capture (MoCap) system in tracking ankle movements, in particular dorsiflexion and plantarflexion. By using IMU sensor (BMI160) and processing the data with a Kalman filter, the proposed methodology aims to accurately estimate the orientation angle: roll, pitch, and yaw. The comparison shows high agreement between the IMU and MoCap systems, with an average cosine similarity of 0.9831 and an average Root Mean Square Error (RMSE) of 5.35%. These results demonstrate that the proposed protocol offers a reliable cost-effective solution for real-time ankle motion monitoring, making it a promising tool for rehabilitation, remote patient monitoring, and wearable motion assessment, particularly benefiting elderly individuals.

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A Feasibility Study for a Cost-Effective Wearable System for Real-Time Ankle Mobility Monitoring

  • Giovanni Mastrangelo,
  • Betsy Dayana Marcela Chaparro Rico,
  • Matteo Russo,
  • Marco Ceccarelli,
  • Daniele Cafolla

摘要

As the aging population continues to grow, the demand for accessible cost-effective solutions for rehabilitation and mobility monitoring becomes increasingly urgent. The work presents a new protocol using easy-to-wear sensors that will enable continuous real-time tracking of ankle mobility and muscle performance. A wearable system is designed as based on Inertial Measurement Units (IMU) for real-time ankle mobility tracking, aiming to provide an affordable alternative to traditional high-cost motion analysis systems. The system’s performance is compared to the gold-standard Motion Capture (MoCap) system in tracking ankle movements, in particular dorsiflexion and plantarflexion. By using IMU sensor (BMI160) and processing the data with a Kalman filter, the proposed methodology aims to accurately estimate the orientation angle: roll, pitch, and yaw. The comparison shows high agreement between the IMU and MoCap systems, with an average cosine similarity of 0.9831 and an average Root Mean Square Error (RMSE) of 5.35%. These results demonstrate that the proposed protocol offers a reliable cost-effective solution for real-time ankle motion monitoring, making it a promising tool for rehabilitation, remote patient monitoring, and wearable motion assessment, particularly benefiting elderly individuals.