Design and Feasibility Study of a Leg-exoskeleton Assistive Wheelchair Robot with Tests on Gluteus Medius Muscles.

Journal: Sensors (Basel, Switzerland)
PMID:

Abstract

The muscles of the lower limbs directly influence leg motion, therefore, lower limb muscle exercise is important for persons living with lower limb disabilities. This paper presents a medical assistive robot with leg exoskeletons for locomotion and leg muscle exercises. It also presents a novel pedal-cycling actuation method with a crank-rocker mechanism. The mechanism is driven by a single motor with a mechanical structure that ensures user safety. A control system is designed based on a master-slave control with sensor fusion method. Here, the intended motion of the user is detected by pedal-based force sensors and is then used in combination with joystick movements as control signals for leg-exoskeleton and wheelchair motions. Experimental data is presented and then analyzed to determine robotic motion characteristics as well as the assistance efficiency with attached electromyogram (EMG) sensors. A typical muscle EMG signal analysis shows that the exercise efficiency for EMG activated amplitudes of the gluteus medius muscles approximates a walking at speed of 3 m/s when cycling at different speeds (i.e., from 16 to 80 r/min) in a wheelchair. As such, the present wheelchair robot is a good candidate for enabling effective gluteus medius muscle exercises for persons living with gluteus medius muscle disabilities.

Authors

  • Gao Huang
    Department of Automation, Tsinghua University, Beijing 100084, China. huang-g09@mails.tsinghua.edu.cn
  • Marco Ceccarelli
    Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, 100081, China. ceccarelli@unicas.it.
  • Qiang Huang
    Department of Orthopedics, West China Hospital, Sichuan University, Chengdu Sichuan, 610041, P.R.China.
  • Weimin Zhang
    School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China.
  • Zhangguo Yu
    Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, 100081, China. yuzg@bit.edu.cn.
  • Xuechao Chen
    Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, 100081, China. chenxuechao@bit.edu.cn.
  • Jingeng Mai