https://www.researchgate.net/publication/398726208_Integrating_physiotherapy_into_social_prescribing_pathways_for_chronic_pain_management exercise science and kinesiology

Unique Title: “Digital Biomarkers of Motor Control and Cortical Activity in Chronic Pain: A Dual-Modal Machine Learning Approach to Exercise Prescription and Triage” Abstract: Chronic pain presents a complex challenge to exercise prescription and movement rehabilitation, often requiring objective measures of motor performance and physiological state to guide intervention. This study explored the utility of digital kinematic and electroencephalographic biomarkers in classifying exercise execution quality and pain-related cortical activity within a kinesiology framework. Using publicly available datasets, trunk rotation kinematics from 21 adults with chronic low back pain and resting-state EEG from 100 individuals with persistent pain were analyzed. Machine learning models, including logistic regression, support vector machines, and gradient boosting, were trained on extracted movement features (range of motion, smoothness, symmetry, jerk, inter-segmental coordination) and neurophysiological features (frontal alpha asymmetry, global connectivity, sample entropy, aperiodic exponents). Results demonstrated near-perfect classification of correct versus incorrect exercise performance (AUC = 1.00), with key kinematic predictors including shoulder abduction angle, movement symmetry, and jerk. EEG-based classification of high versus low pain states was also strong (AUC = 0.97), driven by theta and alpha band connectivity, frontal asymmetry, and signal entropy. These findings suggest that multimodal digital assessment can reliably quantify movement proficiency and cortical state in chronic pain, offering a data-driven foundation for exercise triage, personalized movement prescription, and integration into community-based physical activity pathways. This work highlights the convergence of motor control science, exercise physiology, and computational kinesiology in advancing precision rehabilitation for chronic pain populations.