Applied Smart Rehabilitation Technologies and AI-Driven Neuromuscular Assessment in Physical Therapy

Dear Colleagues,

Rapid advancements in digital health, wearable sensors, robot-assisted therapy, and AI-driven analytic technologies are transforming the fields of physical therapy and neuromuscular rehabilitation. Novel tools such as smart rehabilitation devices, surface EMG analytics, sensor-integrated exoskeletons, and intelligent stimulation systems enable clinicians and researchers to measure movement quality, neuromuscular function, and treatment response with unprecedented precision.

This Special Issue aims to gather innovative, multidisciplinary research that explores smart technologies for assessment, monitoring, and intervention in physical therapy. We welcome studies utilizing wearable and ambient sensors, machine learning–based movement analysis, robotics for motor recovery, predictive models of neuromuscular performance, and technology-assisted therapeutic strategies across various populations and conditions. Contributions that bridge engineering, neuroscience, physical therapy, and computational science are particularly encouraged.

We invite original research, clinical trials, pilot studies, technical reports, review papers, and systematic reviews that investigate cutting-edge methods to enhance rehabilitation outcomes.

Topics of interest include, but are not limited to, the following:

• AI-driven movement and gait analysis;
• Wearable sensor systems (EMG, IMU, pressure sensors, bio-signals) for neuromuscular assessment;
• Smart rehabilitation robots and exoskeleton-based interventions;
• Intelligent electrical stimulation or biofeedback systems;
• Predictive modeling of motor recovery, pain, or neuromuscular function;
• Digital therapeutics and home-based remote rehabilitation;
• Machine learning–enhanced evaluation of physical therapy outcomes;
• Technology-supported interventions for aging populations;
• Integrative biomechanical and physiological data analytics;

We look forward to receiving contributions that advance the future of technology-enhanced rehabilitation and support evidence-based, personalized care in physical therapy.

Prof. Dr. Sanghun Jang
Guest Editor

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