Toward Multimodal Human-Robot Interaction to Enhance Active Participation of Users in Gait Rehabilitation

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 25; no. 11; pp. 2054 - 2066
• Main Authors: Gui, Kai, Liu, Honghai, Zhang, Dingguo
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Active control; active participation; Admittance; Adult; Algorithms; Biomechanical Phenomena; Brain; brain-computer interface; Brain-Computer Interfaces; Central pattern generator; Central Pattern Generators; Cognitive ability; Cognitive human-robot interaction; Electrical impedance; Electromyography; Evoked Potentials, Somatosensory; Exoskeleton; Exoskeleton Device; Exoskeletons; Gait; Gait Disorders, Neurologic - rehabilitation; gait rehabilitation; Healthy Volunteers; Human motion; Human-robot interaction; Humans; Leg; Locomotion; Male; Motivation; Paraplegia; Patient Participation; Patients; physical human-robot interaction; Rehabilitation; Retraining; Rhythms; Robotics; Robots; Stroke; Stroke Rehabilitation - instrumentation; Stroke Rehabilitation - methods; Training; Trajectory
• ISSN: 1534-4320; 1558-0210; 1558-0210
• DOI: 10.1109/TNSRE.2017.2703586

Robotic exoskeletons for physical rehabilitation have been utilized for retraining patients suffering from paraplegia and enhancing motor recovery in recent years. However, users are not voluntarily involved in most systems. This paper aims to develop a locomotion trainer with multiple gait patterns, which can be controlled by the active motion intention of users. A multimodal human-robot interaction (HRI) system is established to enhance subject's active participation during gait rehabilitation, which includes cognitive HRI (cHRI) and physical HRI (pHRI). The cHRI adopts brain-computer interface based on steadystate visual evoked potential. The pHRI is realized via admittance control based on electromyography. A central pattern generator is utilized to produce rhythmic and continuous lower joint trajectories, and its state variables are regulated by cHRI and pHRI. A custom-made leg exoskeleton prototype with the proposed multimodal HRI is tested on healthy subjects and stroke patients. The results show that voluntary and active participation can be effectively involved to achieve various assistive gait patterns.