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A Wearable Device for Monitoring Muscle Condition During Exercise

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Intelligent Information and Database Systems (ACIIDS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1178))

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Abstract

In recent years, the wearable devices have been popularly applied in the health care field, which usually is worn on the wrist, like as a sport band, and an ECG patch. The common functions for these wearable devices are to display the body condition in real time, and have a small size. Therefore, two challenges in the development of the wearable device have to be overcome. First problem is the power consumption, and the second problem is the time of digital signal processing in the microcontroller system. The electromyogram (EMG) signal represents the condition of the muscle activity, which could be used to determine the degree of muscle fatigue. In this study, the goal is to develop an EMG patch which could be worn on any muscle to detect the muscle condition in real time when exercising. A Cortex-M4 microcontroller was used to calculate the median frequency of EMG which represents the muscle condition. In order to denoise the EMG signal, the empirical mode decomposition method was also used and run in this microcontroller. Two electrodes circuit was designed to measure the EMG which only used one instrument amplifier and two integrated circuits of operation amplifier. We compared the median frequency of EMG signal calculated by the microcontroller in the real time and personal computer in the off line, which different root mean square was only 3.72 Hz. Therefore, the EMG patch designed in this study could be applied to monitor the muscle condition when doing the exercise.

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Acknowledgment

This research was funded by the Ministry of Science and Technology in Taiwan under MOST 107-2221-E-324-001.

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Correspondence to Shing-Hong Liu .

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Liu, SH., Huang, J., Huang, YF., Tan, TH., Huang, TS. (2020). A Wearable Device for Monitoring Muscle Condition During Exercise. In: Sitek, P., Pietranik, M., Krótkiewicz, M., Srinilta, C. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Communications in Computer and Information Science, vol 1178. Springer, Singapore. https://doi.org/10.1007/978-981-15-3380-8_35

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  • DOI: https://doi.org/10.1007/978-981-15-3380-8_35

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3379-2

  • Online ISBN: 978-981-15-3380-8

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