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November 2020

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Thu, 19 Nov 2020 18:59:43 +0000
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Notice and Invitation
Oral Presentation of Dissertation Proposal
Department of Bioengineering, George Mason University

Joseph Majdi

BSE in Biomedical Engineering, Tulane University, 2012
MS in Biomedical Engineering, Tulane University, 2012
MS in Electrical and Computer Engineering, George Mason University, 2017


Using Ultrasound to Detect Muscle Fatigue


Monday, November 30, 2020, 1:30 – 3:30 pm
Via Zoom<https://gmu.zoom.us/j/91526317897?pwd=M3ZLL3BDOXpzblI1NjZqQUhBek11QT09>
All are invited to attend.


Committee
Dr. Siddhartha Sikdar, Dissertation Director
Dr. Parag Chitnis, Committee Chair
Dr. Shani Ross
Dr. Eugene Civillico



Abstract:

Functional electrical stimulation (FES) is often used for rehabilitation in movement disorders and in assistive devices such as exoskeletons. However, FES can rapidly cause muscle fatigue, which limits the induced force production. At present there exists no reliable, real time indicator for FES-induced muscle fatigue. We believe that functional muscle physiology associated with muscle fatigue can be inferred from ultrasound imaging. In this study, we utilized tissue Doppler imaging (TDI) to quantify FES-induced twitch responses in the gastrocnemius muscle, at baseline and after inducing fatigue through repeated voluntary isometric contractions. We estimated muscle velocities using M-mode TDI to quantify differences in the twitch response before and after fatigue. Preliminary results indicate that fatigue induces a higher muscle acceleration during twitch, and the muscle contracts for a longer duration. These results could potentially be used as a real-time indicator for muscle fatigue. We are investigating the use of such a system integrated into an external hybrid walking exoskeleton that can switch from FES-induced force generation to external motors for force generation once the muscle fatigues. Further, it may be possible to replace TDI imaging with a wearable single-element continuous wave Doppler instrument for these measurements, reducing computational complexity and power requirements.



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