Robotic Rehabilitation

Robotic rehabilitation aims to restore motor function in individuals with impairments like stroke, using robots to deliver targeted, repetitive therapy. Current research emphasizes improving the accuracy and adaptability of these systems through advanced control architectures (e.g., admittance-type virtual fixtures, assist-as-needed controllers), machine learning techniques (e.g., meta-learning, federated learning, LSTM-Transformers) for personalized therapy, and enhanced sensor integration (e.g., EMG, EEG, tactile feedback) to better interpret user intent and provide more effective assistance. This field holds significant promise for improving patient outcomes and reducing the burden on healthcare systems by providing efficient, personalized, and engaging rehabilitation.