应用于体感诱发电位的多参考自适应噪声消除

Multireference adaptive noise cancellation applied to somatosensory evoked potentials.

作者信息

Parsa V, Parker P A

机构信息

Institute of Biomedical Engineering, University of New Brunswick, Fredericton, Canada.

出版信息

IEEE Trans Biomed Eng. 1994 Aug;41(8):792-800. doi: 10.1109/10.310094.

DOI:10.1109/10.310094

PMID:7927401

Abstract

Somatosensory Evoked Potentials (SEP's) contain information that is useful in diagnosing various physiological disorders. However, surface measurements of these potentials suffer from very poor Signal-to-Noise ratio (SNR) resulting in imperceptible SEP waveforms. This factor motivates the employment of dedicated signal processing techniques to improve the quality of the waveform. The objective of this research work is to improve the SNR of SEP by eliminating the predominant myoelectric interference. The strategy followed to achieve this goal is to process the SEP signal by MultiReference Adaptive Noise Cancellation (MRANC). A theoretical model for the MRANC is presented and its performance under the influence of various factors is investigated and compared with other signal processing techniques. The performance of the MRANC is then evaluated by processing simulated and in vivo SEP data. It is found that the MRANC gives a significant improvement in the SNR of the SEP.

摘要

体感诱发电位（SEP）包含有助于诊断各种生理紊乱的信息。然而，这些电位的表面测量存在非常低的信噪比（SNR），导致SEP波形难以察觉。这一因素促使采用专门的信号处理技术来提高波形质量。这项研究工作的目标是通过消除主要的肌电干扰来提高SEP的信噪比。为实现这一目标所采用的策略是通过多参考自适应噪声消除（MRANC）处理SEP信号。提出了MRANC的理论模型，并研究了其在各种因素影响下的性能，并与其他信号处理技术进行了比较。然后通过处理模拟和体内SEP数据来评估MRANC的性能。结果发现，MRANC在SEP的信噪比方面有显著提高。