Postoperative healing patterns in elbow using electromyography: Towards the development of a wearable mechatronic elbow brace

Musculoskeletal (MSK) conditions are the most common cause of severe long-term pain and physical disability. Current postoperative treatment for patients requires them to follow a long-term physiotherapy program customized for each specific case; however, this process can be complex, time-consuming...

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Bibliographic Details
Main Authors: Haddara, Raneem, Yue Zhou, Chinchalkar, Shrikant, Trejos, Ana Luisa
Format: Conference Proceeding
Language:English
Subjects:
Arm Injuries - rehabilitation
Braces
Elbow
Elbow - physiopathology
Elbow - surgery
Electromyography
Electromyography - instrumentation
Electromyography - methods
Humans
Medical treatment
Muscle Contraction - physiology
Muscle, Skeletal - physiology
Muscles
Sociology
Statistics
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Summary:Musculoskeletal (MSK) conditions are the most common cause of severe long-term pain and physical disability. Current postoperative treatment for patients requires them to follow a long-term physiotherapy program customized for each specific case; however, this process can be complex, time-consuming and without the right therapy it may end up being ineffective. A possible solution involves the development of wearable mechatronic elbow braces that use electromyography (EMG) to identify patient intent. However, EMG characteristics change based on the health of the individual and therefore require further investigation. In order to quantify the progress of MSK injury patients and assess their neuromuscular health, EMG signals from 16 healthy individuals and 15 postoperative patients were collected and analyzed. The experiments conducted show that EMG can be used as a method for assessing MSK health. A normal range across the muscle groups has been identified to which the patient population was compared. This showed statistically significant differences in the magnitudes of muscle recruitment and activation between the two groups. Furthermore, a comparison within the patient population at the beginning of their therapy versus at the end of their therapy was conducted. Statistical differences arose in this second analysis further proving that patients' signals tend to change and show trends closer to those of the healthy population.
ISSN:1945-7901
DOI:10.1109/ICORR.2017.8009443