Dai Ji-tao

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About

Dai Ji-tao is a researcher focused on rehabilitation robotics and biomedical signal processing, with a particular emphasis on surface electromyography (sEMG) for upper limb motor recovery. His work centers on developing intelligent systems that interpret muscle activity to control robotic rehabilitation devices, aiming to restore function in individuals with hemiplegia or other motor impairments. In two highly cited papers from 2018, each garnering 11 citations, Dai made significant contributions to the field. One study introduced a novel sEMG-based pattern recognition method for shoulder-elbow composite motion, employing a fusion of autoregressive model coefficients and wavelet features to enhance control accuracy for upper limb rehabilitation robots. The other paper detailed the design of a comprehensive hemiplegic rehabilitation training system, integrating an upper limb robot with pattern recognition and motion control for both single and multi-degree-of-freedom exercises. These works demonstrate Dai’s impact in advancing human-robot interaction for neurorehabilitation, providing practical frameworks for assistive technologies that respond to a patient’s own physiological signals. His research bridges engineering and clinical application, offering promising pathways for more adaptive, user-responsive rehabilitation solutions.