Masters Applied Projects

Project 3

Motor Unit Decomposition from HD-EMG Measurements Recorded from the Forearm During Finger Contraction

Student:

Spencer Cobb

Mentors:

Dr. Stephen Helms Tillery - SBHSE

Dr. Jitendran Muthuswamy - SBHSE

Dr. Marco Santello – SBHSE

YouTube Link:
View the video link below before joining the zoom meeting

Zoom link:
https://asu.zoom.us/j/286 955 4024

Abstract:

Motor units (MUs) are made up of a motor neuron and the skeletal muscle fibers that the motor neuron innervates. In this study, we hypothesize that high-density (HD) electromyographic (EMG) signal collected from forearm muscles during individuated finger force production can be decomposed into single motor units. To test this hypothesis, we developed an apparatus with four individual force/torque sensors (one per finger) and used an HD-EMG electrode array placed on the forearm. The EMG signals were amplified and analyzed offline for MU decomposition using a MATLAB code. Subjects were asked to exert 10% to 30% of their maximum voluntary force contraction (MVCF) with each fingertip in 5% increments. The force applied to the sensors was mapped to the movement of a cursor on the screen in front of the subject. In each trial, subjects were asked to move the cursor to track a line on the screen over a 60-s period. Force and EMG data were recorded at a sampling frequency of 2048 Hz. Trials were conducted twice for each MVCF, and the order of target force and finger was presented in a pseudo-random order. We found that the number of MUs that could be decomposed decreased with the magnitude of the target force, with an average of 6.5 and 3.3 MUs being decomposed at 10% and 30% MVCF, respectively. Future work will address factors that can improve MU decomposition at higher finger forces and tracking a given MU across different task conditions, e.g., target force or individuated versus multi-digit force production.