Abstract
Objective To efficiently detect somsatosensory evoked potential (SEP) using field programmable gate array (FPGA) real-time system, fixed-point algorithm based adaptive noise canceller (ANC) was designed to improve signal to noise ratio (SNR). Methods With the optimization of important parameters that influence the performance of fixed-point algorithm ANC, the performance was compared to that of floating-point algorithm ANC which was isolated from the effect of quantization error. Results In the simulation study, the outputs of fixed-point-based ANC showed a little higher distortion from real SEP signals than that of floating-point algorithm ANC. In the optimal selection of μ value, fixed-point algorithm ANC could get as good results as floating-point algorithm. Conclusion With appropriate parameter values, fixed-point algorithm ANC is able to improve SNR of SEP as well as that of fixed-point algorithm ANC. Key words: Somsatosensory evoked potential; Fixed-point algorithm; Adaptive noise canceller; Step-size parameter, Distortion index
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