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Sensors 2014, 14(7), 12410-12424; doi:10.3390/s140712410
Article

A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement

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Received: 27 March 2014; in revised form: 10 June 2014 / Accepted: 7 July 2014 / Published: 10 July 2014
(This article belongs to the Section Physical Sensors)
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Abstract: A real-time muscle fatigue monitoring system was developed to quantitatively detect the muscle fatigue of subjects during cycling movement, where a fatigue progression measure (FPM) was built-in. During the cycling movement, the electromyogram (EMG) signals of the vastus lateralis and gastrocnemius muscles in one leg as well as cycling speed are synchronously measured in a real-time fashion. In addition, the heart rate (HR) and the Borg rating of perceived exertion scale value are recorded per minute. Using the EMG signals, the electrical activity and median frequency (MF) are calculated per cycle. Moreover, the updated FPM, based on the percentage of reduced MF counts during cycling movement, is calculated to measure the onset time and the progressive process of muscle fatigue. To demonstrate the performance of our system, five young healthy subjects were recruited. Each subject was asked to maintain a fixed speed of 60 RPM, as best he/she could, under a constant load during the pedaling. When the speed reached 20 RPM or the HR reached the maximal training HR, the experiment was then terminated immediately. The experimental results show that the proposed system may provide an on-line fatigue monitoring and analysis for the lower extremity muscles during cycling movement.
Keywords: electromyogram; muscle fatigue; cycling movement; median frequency; fatigue progression measure electromyogram; muscle fatigue; cycling movement; median frequency; fatigue progression measure
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Chen, S.-W.; Liaw, J.-W.; Chan, H.-L.; Chang, Y.-J.; Ku, C.-H. A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement. Sensors 2014, 14, 12410-12424.

AMA Style

Chen S-W, Liaw J-W, Chan H-L, Chang Y-J, Ku C-H. A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement. Sensors. 2014; 14(7):12410-12424.

Chicago/Turabian Style

Chen, Szi-Wen; Liaw, Jiunn-Woei; Chan, Hsiao-Lung; Chang, Ya-Ju; Ku, Chia-Hao. 2014. "A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement." Sensors 14, no. 7: 12410-12424.



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