Work

Adaptive robotic rehabilitation using muscle fatigue as a trigger

Year: 2019

Type: conference-paper

Abstract: Fatigue is a pervasive symptom following brain injury or disease. It has been known to impact recovery and hence is an important factor in rehabilitation. Robotic rehabilitation may be one way to reduce fatigue because of the robot's capability to adapt to user's performance. This paper explores an adaptive rehabilitation system to provide personalized upper limb rehabilitation. The system collects EMG data from the major muscles responsible for movement and adapts the forces used for rehabilitation (assistive and resistive) in real time based on muscle fatigue. Experimental results and the user survey outcomes show that the system was able to detect the onset of fatigue within ± 10 seconds error margin. Overall, it was found that the subjects experienced lower fatigue and had a higher probability of compliance and engagement with the proposed robotic rehabilitation system.

Source: EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous)

DOI: 10.1145/3360774.3360789

Authors: Varun Kanal, Maher Abujelala, James Brady, Glenn Wylie, Fillia Makedon

Institutions: The University of Texas at Arlington, Kessler Foundation

Language: English

Topic: Prosthetics and Rehabilitation Robotics

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: National Science Foundation