Validation of Low Cost Wearables Sensors in Motor Telerehabilitation Exercises

During the Covid-19 pandemic, telemedicine services enabled healthcare systems to provide treatment to all individuals confined to their homes. Telerehabilitation, a subset of telemedicine, facilitates remote physical or psychiatric rehabilitation, primarily using video calls. To enhance this important service, wearable sensors capable of monitoring physiological and motion parameter, can provide precise insights into patient rehabilitation progress, particularly during rehabilitative exercises. This paper presents the development and validation of a telerehabilitation system based on low-cost wearable sensors that can characterize rehabilitation exercises. Eleven elderly participants (9 female and 2 males; age = 72.6 ± 5.0 years; height = 1.66 ± 0.09 m; mass = 67.8 ± 9.8kg) performed sixteen rehabilitation exercises. In this study, the knee extension in lying position is analysed. Movement characterization was based both on a prototypical sensor and on commercially available sensors used as reference. Individual exercise trials were segmented into single repetitions, and various motor capacity features were computed. Bland e Altmann analysis was performed for each parameter to assess differences between the measurement systems. Results indicate that parameter such as the number of repetitions, repetition time and gesture smoothness can be effectively monitored using our low-cost sensors. Identified errors, possibly attributable to hardware issues, will be addressed through future metrological testing. Despite these challenges, we are optimistic about the accessibility and validity of our system for individualized telerehabilitation solutions.