Skeletal muscle contraction monitoring device
Date of Issue2017
School of Electrical and Electronic Engineering
A Skeletal Muscle Contraction Monitoring Device that used in sports training is realized through detecting and processing the Surface Electromyography (sEMG) signal in this project. The device is made of: ①a front-stage acquiring circuit, which receives the sEMG signal via surface electrodes,②a processing software – LabVIEW that acquire the sample data of sEMG signal from National Instruments PXI-4462 card used as Analog-to-Digital Converter (ADC). Between the electromyography (EMG) signal and the ultrasonic sensor, the former is chosen for implement to monitor muscle contraction due to its low cost and feasibility. Thereafter, the non-invasive surface EMG electrodes are selected for convenience to use as compared with the invasive needle electrodes. The front-stage acquiring circuit, with common-mode rejection amplifier, precision operational amplifier, high-pass filter and 2-stages low-pass filter, is designed to amplify the sEMG signal by around 600 times and filter it to a bandwidth that is between 20 to 500 Hz, approximately. After hardware circuit processing, the amplified and filtered sEMG signal is converted to digital signal through ADC (NI PXI-4462) and analyzed by LabVIEW to obtain its features for further analysis. The performance of device’s characteristics is investigated by numerous simulations and experiments. And, the results show that a rough sEMG signal acquired from human skin can be detected and observed after amplified and filtered through front-stage circuit. Additionally, the features of sEMG signal are clearly presented in the analyzed results after converted to digital signal and processed by LabVIEW. Experiments and tests were conducted to validate the ability of this device to monitor muscle contractions. Different amplitudes of sEMG represent different muscle movements of human body. Other features of sEMG signal are also analyzed for further application in the area of kinesics and clinical medicine.
DRNTU::Engineering::Electrical and electronic engineering