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Mechanomyography-based muscle fatigue detection during electrically elicited cycling in patients with spinal cord injury

Naeem, Jannatul and Hamzaid, Nur Azah and Islam, Md. Anamul and Azman, Amelia Wong and Bijak, Manfred (2019) Mechanomyography-based muscle fatigue detection during electrically elicited cycling in patients with spinal cord injury. Medical and Biological Engineering and Computing, 57 (6). pp. 1199-1211. ISSN 0140-0118 E-ISSN 1741-0444 (Unpublished)

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Patients with spinal cord injury (SCI) benefit from muscle training with functional electrical stimulation (FES). For safety reasons and to optimize training outcome, the fatigue state of the target muscle must be monitored. Detection of muscle fatigue from mel frequency cepstral coefficient (MFCC) feature of mechanomyographic (MMG) signal using support vector machine (SVM) classifier is a promising new approach. Five individuals with SCI performed FES cycling exercises for 30 min. MMG signals were recorded on the quadriceps muscle group (rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM)) and categorized into non-fatigued and fatigued muscle contractions for the first and last 10 min of the cycling session. For each subject, a total of 1800 contraction-related MMG signals were used to train the SVM classifier and another 300 signals were used for testing. The average classification accuracy (4-fold) of non-fatigued and fatigued state was 90.7% using MFCC feature, 74.5% using root mean square (RMS), and 88.8% with combined MFCC and RMS features. Inter-subject prediction accuracy suggested training and testing data to be based on a particular subject or large collection of subjects to improve fatigue prediction capacity.

Item Type: Article (Journal)
Additional Information: 4858/76358
Uncontrolled Keywords: Functional electrical stimulation; Mechanomyography; Mel frequency cepstral coefficients (MFCC); Muscle fatigueSpinal cord injury
Subjects: Q Science > QP Physiology
R Medicine > RD Surgery
T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Amelia Wong Azman
Date Deposited: 19 Nov 2019 16:51
Last Modified: 19 Nov 2019 16:51
URI: http://irep.iium.edu.my/id/eprint/76358

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