https://www.researchgate.net/publication/398601865_An_M-Health_Algorithmic_Approach_to_[…]B1YmxpY2F0aW9uIiwicHJldmlvdXNQYWdlIjoic2NpZW5jZVRvcGljIn19 exercise science and kinesiology

Title: A Novel Kinematic Biofeedback Framework for Automating Qualitative Assessment of Corrective Therapeutic Movement Abstract: Traditional therapeutic exercise adherence and form monitoring rely on subjective clinician observation, presenting a significant barrier to effective remote rehabilitation. This paper introduces a domain-specific algorithmic framework designed to automate the qualitative assessment of corrective exercise. By modeling movement sequences as discrete pose chains, the system captures fundamental joint kinematics in real-time and maps them against clinically prescribed movement patterns. The core innovation is the application of a modified sequence alignment metric to identify both global movement fidelity and local kinematic deviations, such as improper joint angle timing or amplitude. This approach provides granular, objective feedback on movement accuracy — a critical determinant of therapeutic efficacy in musculoskeletal rehabilitation. The client-side implementation ensures accessibility and scalability for remote kinesiology applications, offering a step toward bridging the gap between clinical instruction and independent home exercise practice.