Towards Precision Physiotherapy for Chronic Low Back Pain: A Comprehensive Review of Hybrid Fuzzy Logic and Artificial Neural Network Models

Chronic low back pain (CLBP) is a major cause of disability, with substantial variability in patient characteristics and rehabilitation outcomes. Hybrid Fuzzy Logic-Artificial Neural Network (FL-ANN) models offer a promising approach to precision physiotherapy by combining uncertainty handling, nonlinear learning, and adaptive prediction. This review examines FL-ANN, ANFIS, machine learning, and deep learning approaches for CLBP assessment, outcome prediction, and personalized rehabilitation. Emerging technologies, including wearable sensors, electromyography, gait analysis, Explainable AI, IoT, digital twins, and federated learning, are also discussed. Despite challenges in data quality, clinical validation, interpretability, and implementation, hybrid intelligent models show strong potential for personalized rehabilitation and clinical decision support in CLBP management.