TY - JOUR
T1 - An ultra-low power surface emg sensor for wearable biometric and medical applications
AU - Wu, Yi Da
AU - Ruan, Shanq Jang
AU - Lee, Yu Hao
N1 - Funding Information:
Funding: This research was funded by the National Taiwan University of Science and Technology— Taipei Medical University Joint Research Program under the project “The design of musical canter algorithm based on deep learning” (Grant No. NTUST-TMU-110-02).
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/11
Y1 - 2021/11
N2 - In recent years, the surface electromyography (EMG) signal has received a lot of attention. EMG signals are used to analyze muscle activity or to evaluate a patient’s muscle status. However, commercial surface EMG systems are expensive and have high power consumption. Therefore, the purpose of this paper is to implement a surface EMG acquisition system that supports high sampling and ultra-low power consumption measurement. This work analyzes and optimizes each part of the EMG acquisition circuit and combines an MCU with BLE. Regarding the MCU power saving method, the system uses two different frequency MCU clock sources and we proposed a ping-pong buffer as the memory architecture to achieve the best power saving effect. The measured surface EMG signal samples can be forwarded immediately to the host for further processing and additional application. The results show that the average current of the proposed architecture can be reduced by 92.72% compared with commercial devices, and the battery life is 9.057 times longer. In addition, the correlation coefficients were up to 99.5%, which represents a high relative agreement between the commercial and the proposed system.
AB - In recent years, the surface electromyography (EMG) signal has received a lot of attention. EMG signals are used to analyze muscle activity or to evaluate a patient’s muscle status. However, commercial surface EMG systems are expensive and have high power consumption. Therefore, the purpose of this paper is to implement a surface EMG acquisition system that supports high sampling and ultra-low power consumption measurement. This work analyzes and optimizes each part of the EMG acquisition circuit and combines an MCU with BLE. Regarding the MCU power saving method, the system uses two different frequency MCU clock sources and we proposed a ping-pong buffer as the memory architecture to achieve the best power saving effect. The measured surface EMG signal samples can be forwarded immediately to the host for further processing and additional application. The results show that the average current of the proposed architecture can be reduced by 92.72% compared with commercial devices, and the battery life is 9.057 times longer. In addition, the correlation coefficients were up to 99.5%, which represents a high relative agreement between the commercial and the proposed system.
KW - Biosensor devices and interface circuit
KW - EMG acquisition system
KW - Power consumption
KW - Wireless transmission
UR - http://www.scopus.com/inward/record.url?scp=85118500933&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85118500933&partnerID=8YFLogxK
U2 - 10.3390/bios11110411
DO - 10.3390/bios11110411
M3 - Article
C2 - 34821627
AN - SCOPUS:85118500933
SN - 0956-5663
VL - 11
JO - Biosensors
JF - Biosensors
IS - 11
M1 - 411
ER -