A Biologically Inspired Exoskeleton System Capable of Enhancing Human Walking

  • Lingyun Yan

Student thesis: Phd


The lower limb exoskeleton has been widely applied in different fields, such as rehabilitation, training, and the military, which generally improves the performance of subjects. In this study, we developed a lower limb cable-driven soft exoskeleton called MCR Exo that assists walking by reducing lower-limb muscle activity. The MCR Exo mainly contains three systems: sensory system, control system and actuation system. The sensory system collects foot’s kinematic data by digital insole and sends it to the control system. At the same time, the control system identifies the human’s motion pattern and commands the actuation system to supply corresponding assistance. The control system, actuation system and battery are integrated into a custom backpack while the sensors are inserted in the digital insole. The structure of the MCR Exo was designed based on the analysis of the lower-limb muscle forces during walking. The drive system can provide a torque of 10.7 Nm, meeting the lower limb joint moment requirements. The cable actuation path arranged corresponding to the muscle distribution that produces the largest force in the gait cycle. Moreover, a musculoskeletal model simulation calculates the muscle force value. The proposed Exo can detect five gait events, nine activities and recognize a 0-10 km/h walking speed with 99.6% accuracy, 96.8% accuracy and 0.1008 MSE, respectively. Meanwhile, the Exo includes three control strategies for walking assistance: finite state machine (FSM), position profile (PP) and torque profile (TP). A human trial experiment is conducted to analyse the performance of the MCR Exo by measuring the surface electromyography (sEMG) of lower-limb muscles during walking. In the best performed PP mode, the Exo can achieve the largest muscle activity(%MVIC) reduction at 8.61% in Soleus (SO), 5.64% in Gastrocnemius medial (GM) and 4.78% in Gastrocnemius lateral (GL) compared with walking without Exo.
Date of Award31 Dec 2022
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorZhenmin Zou (Supervisor), Lei Ren (Supervisor) & Wei Guo (Supervisor)

Cite this