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
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Department of Mathematical Sciences
Committee Chair
Stephen Carden
Committee Member 1
Li Li
Committee Member 2
Ionut Iacob
Abstract
(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
1361716500
Catalog Permalink
https://galileo-georgiasouthern.primo.exlibrisgroup.com/permalink/01GALI_GASOUTH/1r4bu70/alma9916469948902950
Recommended Citation
Okonna, Mercy U., "Modelling Muscle Activation Using EMG Signal" (2022). Electronic Theses and Dissertations. 2509.
https://digitalcommons.georgiasouthern.edu/etd/2509
Research Data and Supplementary Material
Yes
