Movement Assessment

Movement assessment research focuses on objectively measuring and analyzing human movement, primarily to detect neurological conditions and improve rehabilitation outcomes. Current efforts leverage deep learning, particularly neural architecture search and sensor fusion techniques, to analyze video and sensor data for accurate and efficient movement classification, often surpassing the performance of single-modality approaches. This work is significant because it promises to improve early diagnosis of conditions like cerebral palsy, enhance accessibility of rehabilitation through home-based systems, and standardize assessment procedures by reducing reliance on expert human assessment.