• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.12
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• pp.708-716
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• 2003

The surface EMG signal detected from voluntarily activated muscles can be used as a control signal for functional electrical stimulation. To use the voluntary EMG signal, it is necessary to eliminate the muscle response evoked by the electrical stimulation and enable to process the algorithm in real time. In this paper, we propose the Gram-Schmidt(GS) algorithm and implement it in FPGA(field programmable gate array). GS algorithm is efficient to eliminate periodic signals like muscle response, and is more stable and suitable to FPGA implementations than the conventional least-square approach, due to the systolic array structure.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.34-38
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• 1991

This paper describes and discusses the employment of EMG pattern analysis to provide upper-motor-neuron paraplegics with patient-responsive control of FES (functional electrical stimulation) for the purpose of walker-supported walking. The use of above - lesion EMG signals as a solution to the control problem is considered. The AR (autoregressive) parameters are identified by Kalman filter algorithm using DSP chip and classified by fuzzy theory. The control and stimuli part of the below-lesion are based on microprocessor(8031). The designed stimulator is a 4-channel version. The experiments described above have only attempted to discriminate between standing function and sit-down function. A further advantage of the this system is applied for motor rehabilitation of social readaption of paralyzed humans.