An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise.
Adult
Algorithms
Bicycling
Electromyography
/ instrumentation
Equipment Design
Exercise
/ physiology
Female
Healthy Volunteers
Humans
Male
Monitoring, Physiologic
/ instrumentation
Muscle Contraction
Muscle Fatigue
/ physiology
Signal Processing, Computer-Assisted
Wearable Electronic Devices
Young Adult
application program
electromyogram
muscle fatigue
patch
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
14 Jul 2019
14 Jul 2019
Historique:
received:
21
05
2019
revised:
07
07
2019
accepted:
12
07
2019
entrez:
25
7
2019
pubmed:
25
7
2019
medline:
8
1
2020
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 31337107
pii: s19143108
doi: 10.3390/s19143108
pmc: PMC6679275
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Ministry of Science and Technology, Taiwan
ID : MOST107-2221-E-324-001
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