PRECISION NEUROREHABILITATION IN NEUROLOGICAL PHYSICAL THERAPY FROM FUNCTIONAL ASSESSMENT TO PERSONALIZED MOTOR RECOVERY

Abstract

Neurological disorders produce heterogeneous motor impairments and recovery trajectories, challenging standardized approaches to neurological physical therapy. Precision neurorehabilitation offers a patient-specific framework that integrates objective functional assessment, predictive analytics, and adaptive interventions to optimize motor recovery. This review synthesizes current advances in precision neurorehabilitation across the continuum from functional assessment to individualized therapeutic decision-making. Particular attention is given to digital and sensor-based assessment, quantitative gait and balance analysis, wearable movement biomarkers, artificial intelligence (AI)-assisted prediction, individualized therapeutic exercise, robotics and exoskeletons, virtual reality (VR), brain-computer interfaces (BCIs), neuromodulation, and telerehabilitation. Digital technologies enable continuous and objective characterization of motor behavior beyond episodic clinical assessment, while wearable sensors and machine-learning approaches facilitate longitudinal monitoring and identification of patient-specific recovery patterns. AI-based models further support prognosis, patient stratification, and potentially dynamic adaptation of rehabilitation strategies. Robotics, VR, and BCIs provide opportunities for intensive, repetitive, feedback-driven, and increasingly individualized motor training. Collectively, these technologies support a transition toward closed-loop rehabilitation in which patient performance is continuously measured, interpreted, and used to modify therapeutic interventions. However, clinical translation remains constrained by heterogeneous protocols, small study populations, limited external validation, inconsistent outcomes, cost, interoperability, usability, digital accessibility, and uncertainties regarding long-term effectiveness. Patient safety, algorithmic transparency, clinician oversight, and meaningful patient goals remain fundamental to responsible implementation. Future precision neurorehabilitation should therefore prioritize multicenter validation, standardized outcomes, explainable AI, cost-effectiveness, equitable access, and human-technology collaboration. Integrating multidimensional assessment with adaptive treatment may ultimately enable neurological physical therapy to become more measurable, responsive, patient-centered, and capable of optimizing meaningful motor recovery and functional participation across diverse neurological populations.