Term of Award

Fall 2022

Degree Name

Master of Science in Mathematics (M.S.)

Document Type and Release Option

Thesis (open access)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


Department of Mathematical Sciences

Committee Chair

Stephen Carden

Committee Member 1

Li Li

Committee Member 2

Ionut Iacob


(EMG) is a method for measuring muscle activity by an electrical signal, and is useful in studying motor control, postural control, and in physical therapy. A current research topic is creating an algorithm that can use the EMG signal to reliably classify a muscle as active or inactive. This thesis presents a classification algorithm for leg muscles with a single activation spike while walking. Time is rescaled into steps, which are identified using data from cameras measuring joint angles while walking. The algorithm is based on moving averages and a convex combination of mean signal strength in active and inactive regions. The algorithm is tested on EMG signals from the gastrocnemius, vastus lateralis, and tibialis muscles, using angle measurements from hip, knee, and ankle joints

OCLC Number


Research Data and Supplementary Material


Available for download on Friday, November 17, 2023