Development Of A Portable Muscle Fatigue Analysis System

Muscle fatigue analysis has been widely used in many fields, such as rehabilitation medicine, sport mechanics and ergonomics, etc. Muscle fatigue analysis and evaluation can provide effective guidance for the clinical rehabilitation, sport training and labor work, etc. Surface electromyography (sEMG) can reflect the state of neuromuscular function, and its non-invasive, convenient, objective and many other features, allow it to be an effective tool for analyzing muscle fatigue.Currently, the sEMG-based muscle fatigue analysis focuses on offline processing of data, and some commercially available EMG acquisition devices usually do not include online processing EMG data for fatigue analysis. With this regard, this study developed a portable system for sEMG recording and muscle fatigue analysis. The system has the advantages of small size, low-cost and ease of use, along with the function of real-time analysis of muscle fatigue.The primary contribution of this study include but is not limited to the following:(1) Hardware design of the system. This paper developed a portable system toward muscle fatigue analysis. The system consisted of three modules:signal acquisition and wireless transmission module, data processing module, display and storage module. Signal acquisition module included six bipolar EMG sensors, an analog-to-digital converter (ADC) acquisition circuit, C8051F410(micro-controller unit) MCU module, wireless Bluetooth and power circuits. Data processing module included FPGA core system, wireless Bluetooth, external memory and power circuits. Results display and storage module included ARM core systems, LCD touch screen, SD card circuits and power circuits.(2)Software design of the system. The system software was divided into three modules in terms of their functions:signal acquisition and wireless transmission module, data processing module, display and storage module. Acquisition and wireless transmission module read the EMG collected by ADS1198through MCU, encoded the EMG, sent data to the data processing module through wireless Bluetooth. Data processing module received data through wireless Bluetooth, segmented the EMG data, performed frequency analysis using FFT, calculated six parameters that were used to evaluate muscle fatigue, and sent the result of data to the result display and storage module. The display and storage module was implemented through a customized Windows CE operating system to complete the data reception, data viewing and storage, using LCD touch screen as a user interface.(3) Evaluation of the system performance. The system performance was evaluated via a series of experiments. static sustained muscle contraction was carried out first and then dynamic periodic muscle contraction was performed, to verify the function of muscle fatigue analysis in the proposed system.