Investigation of wearable-based metrics to assess motor performance during telerehabilitation with ARC intellicare

The increasing demand for rehabilitation and remote healthcare solutions has driven the development of telerehabilitation technologies. Among them, wearable inertial sensors (IMUs) offer a promising method for monitoring motor performance. This thesis investigates the implementation of metrics to analyze motor performance during rehabilitation exercises and provide quantitative feedback to caregivers. The study was conducted using inertial data from ARC Intellicare (ARC), a certified telerehabilitation device with five IMU sensors, produced by Henesis. The company provided data from three clinical studies (ARCANGEL, RICOMINCIARE, ARCTRAN) involving healthy controls and individuals with Parkinson’s disease, Multiple Sclerosis, Stroke, and long COVID. Several indicators were implemented and analyzed on the recorded signals, at different levels: from single-repetition metric scores to inter-population analysis. Statistical tests and correlations with clinical scales (MDS-UPDRS, 6MWT) were used to understand whether the chosen indicators could also have an adequate clinical meaning. Results highlight an innovative symmetry indicator (mTADS-SI), based on the Transitional Angular Displacement of a Segment (TADS), which reliably quantifies symmetry and differentiates controls from patients across multiple exercises. Compared to existing studies in the field, this research introduces a novelty by applying the metric to a broad range of movements using a commercially available device. This research underlined the potential of wearable-based motion analysis in telerehabilitation, providing therapists with objective feedback to personalize rehabilitation and remotely monitor patients’ progress. Future works may extend this approach to additional exercises, refining metrics for broader clinical applications.