EMG and EPP-Integrated Human–Machine Interface Between the Paralyzed and Rehabilitation Exoskeleton

Abstract

Although a lower extremity exoskeleton shows great prospect in the rehabilitation of the lower limb, it has not yet been widely applied to the clinical rehabilitation of the paralyzed. This is partly caused by insufficient information interactions between the paralyzed and existing exoskeleton that cannot meet the requirements of harmonious control. In this research, a bidirectional human-machine interface including a neurofuzzy controller and an extended physiological proprioception (EPP) feedback system is developed by imitating the biological closed-loop control system of human body. The neurofuzzy controller is built to decode human motion in advance by the fusion of the fuzzy electromyographic signals reflecting human motion intention and the precise proprioception providing joint angular feedback information. It transmits control information from human to exoskeleton, while the EPP feedback system based on haptic stimuli transmits motion information of the exoskeleton back to the human. Joint angle and torque information are transmitted in the form of air pressure to the human body. The real-time bidirectional human-machine interface can help a patient with lower limb paralysis to control the exoskeleton with his/her healthy side and simultaneously perceive motion on the paralyzed side by EPP. The interface rebuilds a closed-loop motion control system for paralyzed patients and realizes harmonious control of the human-machine system.

An EMG-based force prediction and control approach for robot-assisted lower limb rehabilitation

“…Song estimated the assistive torque based on the normalized EMG signals [10], which was also a proportional formula with EMG-torque gain coefficients. Other similar works can also be found in [13] and [7].…”

On the Well-Timed Assistance in Power-Assisted Sit-to-Stand Movement

“…2). Four air cylinders (SMC R CM2B20-50) were installed beneath the seat with 1MPa air supplied by a compressor (JUN-AIR R [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25], and controlled by a solenoid valve (SMC R VQZ1321) synchronously. It can be calculated from the specifications that the exerted force is about 264N per cylinder.…”

ANFIS to estimate damping coefficient from EMG to optimize the interaction force

“…One of the main objectives of a RRD is to obtain a smooth human machine interaction in different phases of gait cycle at the interaction point by considering patient-exoskeleton interaction is bidirectional rather than unidirectional. A design of an effective wearable exoskeleton controller to achieve bidirectional interaction is possible where minimum interaction force is experienced, since patient now become an active element of a closed loop control system [1]. In human body the motor system is a typical closed loop control system where brain and somatic nervous system (SNS) are the controllers that generates necessary signal for muscle which is the actuator and also with a proprioception feedback channel, which is the biological basis of human motion stability.…”