Abstract
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.
Highlights
An increasing amount of research on combining bioelectrical signals with the Internet of Things (IoT) has been undertaken in the last decade
Surface EMG signal detection can be achieved by utilizing wireless technolo Many wireless transmission technologies are available today, such as 2G/3G wireless
TheToultra-low power surface signal acquisition was deas shown in Figure verify the reliability of the proposed system, the system signal-to-noise signed as shown
Summary
An increasing amount of research on combining bioelectrical signals with the Internet of Things (IoT) has been undertaken in the last decade. The surface EMG sensor is able to record muscle activity by using EMG electrodes to measure the changes in the electrical potential between two points of a muscle [5]. Comparisons of commercial products have found that many surface EMG sensors on the market claim to be low-power and high-sampling, the lowest power consumption among these products is up to 46.25 mW [7,8,9,10]. Many researchers have investigated low-power and high sampling surface EMG systems for long-term recording and applied them in different fields. Brunelli et al [4] developed a wireless multi-channel surface EMG prosthetic sampling measurement system, using 240 Kbps speed Bluetooth technology. The research used 32-channel surface EMG sensors to sample gesture signals.
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