EMG Control of an Upper-Limb Rehabilitation Exoskeleton for SCI Affected Users

Robotic rehabilitation for individuals with spinal cord injury (SCI) has been shown to be most effective when the user is motivated and mentally engaged in the execution of therapeutic exercises. Consequently, designers of the human-robot interface are challenged with developing control schemes that can detect user intent and maximize their engagement. Electromyography (EMG) is a promising technique to address this challenge. In this thesis, an EMG control scheme for an upper-limb exoskeleton, the MAHI Exo-II, is designed and tested with a population of able-bodied users, as well as SCI affected subjects. The presented scheme utilizes pattern recognition techniques to monitor the user's muscle activation patterns and select their intended direction of motion in single or multiple degree-of-freedom (DoF) movements of the elbow and wrist joints. The results presented demonstrate that the control scheme was simple to use, highly adaptive across a range of subjects, and accurate in directional classification.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Engineering

Grantor

Rice University

Year dc:date.issued

2018

Author dc:creator

• Dennis, Troy A

Advisor dc:contributor.advisor

• O'Malley, Marcia K

• Rehabilitation Robots
• Electromyography
• Linear Discriminant Analysis
• Classification Algorithms

Statement dc:rights

• Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1911/105710

OAI identifier oai:identifier

oai:repository.rice.edu:1911/105710