Brown, Ellenor (Georgia Institute of Technology), Aomoto, Kazuya (Nara Institute of Science and Technology), Ikeda, Atsutoshi (Nara Institute of Science and Technology), Ogasawara, Tsukasa (Nara institute of science and technology), Yoshitake, Yasuhide (National Institute of Fitness and Sports), Shinohara, Minoru (Georgia Institute of Technology), Ueda, Jun (Georgia Institute of Technology)

Comparison of Ultrasound Muscle Stiffness Measurement and Electromyography towards Validation of an Algorithm for Individual Muscle Control

Scheduled for presentation during the Invited session "Human Assistive Systems and Wearable Robots: Design and Control" (MoCT2), Monday, October 21, 2013, 17:20−17:40, Room 123

6th Annual Dynamic Systems and Control Conference, October 21-23, 2020, Stanford University, Munger Center, Palo Alto, CA

This information is tentative and subject to change. Compiled on April 26, 2024

Abstract

The ability to control individual muscle activity is widely applicable in clinical diagnostics, training, and rehabilitation. Inducing muscle patterns that amplify abnormal muscle coordination can assist with early diagnosis of neuromuscular disorders. Individual muscle control also allows for targeted exercise of muscles weakened by disease, injury, or disuse. The goals of this research are to test a system for individual muscle control and introduce the use of muscle ultrasound as an alternative to electromyography (EMG). The system integrates a computational model of the right upper extremity with a robotic manipulator to predict and control muscle activity. To test the system, subjects gripped the manipulator and isometrically resisted loads applied to the hand. Muscle activity was measured via EMG and ultrasound. The system was able to induce the desired direction of muscle activity change but with limited precision. EMG measurement appeared susceptible to error due to crosstalk in the forearm.