An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise
In recent years, wearable monitoring devices have been very popular in the health care field and are being used to avoid sport injuries during exercise. They are usually worn on the wrist, the same as sport watches, or on the chest, like an electrocardiogram patch. Common functions of these wearable...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/14/3108 |
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| author | Shing-Hong Liu Chuan-Bi Lin Ying Chen Wenxi Chen Tai-Shen Huang Chi-Yueh Hsu |
| author_facet | Shing-Hong Liu Chuan-Bi Lin Ying Chen Wenxi Chen Tai-Shen Huang Chi-Yueh Hsu |
| author_sort | Shing-Hong Liu |
| collection | DOAJ |
| description | In recent years, wearable monitoring devices have been very popular in the health care field and are being used to avoid sport injuries during exercise. They are usually worn on the wrist, the same as sport watches, or on the chest, like an electrocardiogram patch. Common functions of these wearable devices are that they use real time to display the state of health of the body, and they are all small sized. The electromyogram (EMG) signal is usually used to show muscle activity. Thus, the EMG signal could be used to determine the muscle-fatigue conditions. In this study, the goal is to develop an EMG patch which could be worn on the lower leg, the gastrocnemius muscle, to detect real-time muscle fatigue while exercising. A micro controller unit (MCU) in the EMG patch is part of an ARM Cortex-M4 processor, which is used to measure the median frequency (MF) of an EMG signal in real time. When the muscle starts showing tiredness, the median frequency will shift to a low frequency. In order to delete the noise of the isotonic EMG signal, the EMG patch has to run the empirical mode decomposition algorithm. A two-electrode circuit was designed to measure the EMG signal. The maximum power consumption of the EMG patch was about 39.5 mAh. In order to verify that the real-time MF values measured by the EMG patch were close to the off-line MF values measured by the computer system, we used the root-mean-square value to estimate the difference in the real-time MF values and the off-line MF values. There were 20 participants that rode an exercise bicycle at different speeds. Their EMG signals were recorded with an EMG patch and a physiological measurement system at the same time. Every participant rode the exercise bicycle twice. The averaged root-mean-square values were 2.86 ± 0.86 Hz and 2.56 ± 0.47 Hz for the first and second time, respectively. Moreover, we also developed an application program implemented on a smart phone to display the participants’ muscle-fatigue conditions and information while exercising. Therefore, the EMG patch designed in this study could monitor the muscle-fatigue conditions to avoid sport injuries while exercising. |
| first_indexed | 2024-04-14T06:59:52Z |
| format | Article |
| id | doaj.art-16d5c480b988467d92b5af39122cf4e2 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T06:59:52Z |
| publishDate | 2019-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-16d5c480b988467d92b5af39122cf4e22022-12-22T02:06:48ZengMDPI AGSensors1424-82202019-07-011914310810.3390/s19143108s19143108An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During ExerciseShing-Hong Liu0Chuan-Bi Lin1Ying Chen2Wenxi Chen3Tai-Shen Huang4Chi-Yueh Hsu5Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung City 41349, TaiwanDepartment of Information and Communication Engineering, Chaoyang University of Technology, Taichung City 41349, TaiwanBiomedical Information Engineering Laboratory, University of Aizu, Aizu-wakamatsu City, Fukushima 965-8580, JapanBiomedical Information Engineering Laboratory, University of Aizu, Aizu-wakamatsu City, Fukushima 965-8580, JapanDepartment of Industrial Design, Chaoyang University of Technology, Taichung City 41349, TaiwanDepartment of Leisure Services Management, Chaoyang University of Technology, Taichung City 41349, TaiwanIn recent years, wearable monitoring devices have been very popular in the health care field and are being used to avoid sport injuries during exercise. They are usually worn on the wrist, the same as sport watches, or on the chest, like an electrocardiogram patch. Common functions of these wearable devices are that they use real time to display the state of health of the body, and they are all small sized. The electromyogram (EMG) signal is usually used to show muscle activity. Thus, the EMG signal could be used to determine the muscle-fatigue conditions. In this study, the goal is to develop an EMG patch which could be worn on the lower leg, the gastrocnemius muscle, to detect real-time muscle fatigue while exercising. A micro controller unit (MCU) in the EMG patch is part of an ARM Cortex-M4 processor, which is used to measure the median frequency (MF) of an EMG signal in real time. When the muscle starts showing tiredness, the median frequency will shift to a low frequency. In order to delete the noise of the isotonic EMG signal, the EMG patch has to run the empirical mode decomposition algorithm. A two-electrode circuit was designed to measure the EMG signal. The maximum power consumption of the EMG patch was about 39.5 mAh. In order to verify that the real-time MF values measured by the EMG patch were close to the off-line MF values measured by the computer system, we used the root-mean-square value to estimate the difference in the real-time MF values and the off-line MF values. There were 20 participants that rode an exercise bicycle at different speeds. Their EMG signals were recorded with an EMG patch and a physiological measurement system at the same time. Every participant rode the exercise bicycle twice. The averaged root-mean-square values were 2.86 ± 0.86 Hz and 2.56 ± 0.47 Hz for the first and second time, respectively. Moreover, we also developed an application program implemented on a smart phone to display the participants’ muscle-fatigue conditions and information while exercising. Therefore, the EMG patch designed in this study could monitor the muscle-fatigue conditions to avoid sport injuries while exercising.https://www.mdpi.com/1424-8220/19/14/3108electromyogrampatchmuscle fatigueapplication program |
| spellingShingle | Shing-Hong Liu Chuan-Bi Lin Ying Chen Wenxi Chen Tai-Shen Huang Chi-Yueh Hsu An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise Sensors electromyogram patch muscle fatigue application program |
| title | An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise |
| title_full | An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise |
| title_fullStr | An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise |
| title_full_unstemmed | An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise |
| title_short | An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise |
| title_sort | emg patch for the real time monitoring of muscle fatigue conditions during exercise |
| topic | electromyogram patch muscle fatigue application program |
| url | https://www.mdpi.com/1424-8220/19/14/3108 |
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