Mingxu Sun1,#,*, Yinghang Jiang2,3,#, Qi Liu3,4,*, Xiaodong Liu4
CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 67-83, 2019, DOI:10.32604/cmc.2019.06079
Abstract A Functional Electrical stimulation (FES) therapy is a common rehabilitation intervention after stroke, and finite state machine (FSM) has proven to be an effective and intuitive FES control method. The FSM uses the data information generated by the accelerometer to robustly trigger state transitions. In the medical field, it is necessary to obtain highly safe and accurate acceleration data. In order to ensure the accuracy of the acceleration sensor data without affecting the accuracy of the motion analysis, we need to perform acceleration big data calibration. In this context, we propose a method for robustly More >
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