Robotics and Artificial Intelligence in Neuromuscular Performance

Athletic performance increasingly depends on technologies that can measure, model, and guide neuromuscular function across the full athlete lifecycle. Robotics and Artificial Intelligence in Neuromuscular Performance provides an evidence-based framework for applying robotics, artificial intelligence, computer vision, wearable sensing, virtual reality, and biofeedback to assessment, training, injury prevention, rehabilitation, and return-to-play decision-making. Organized across 18 chapters, it links neuromuscular physiology with intelligent athlete systems, moving from foundational concepts in computational biomechanics and robotic dynamometry to applied protocols for load management, injury prediction, exoskeletal resistance, smart rehabilitation, and AI-enhanced clearance decisions. The book is designed for sports scientists, clinicians, physiotherapists, athletic trainers, strength-and-conditioning professionals, biomechanics researchers, and technology developers who need to evaluate rapidly expanding sports technologies with scientific confidence. Rather than treating innovation as inherently beneficial, it gives readers tools for judging validation status, measurement error, algorithmic limitations, data governance, and ethical risk. Its inclusion of the AICICA framework, implementation checklists, and case studies positions it as both a scholarly synthesis and a practical guide for responsible technology adoption in elite, clinical, and research settings.