Keshtkaran Mohammad Reza, Yang Zhi
Department of Electrical and Computer Engineering, National University of Singapore, 117576, Singapore.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:5214-7. doi: 10.1109/EMBC.2012.6347169.
This paper presents an algorithm for removing power line interference in neural recording experiments. It does not require any interference reference signal and can reliably track interference changes in frequency, phase, and amplitude. The method includes three major steps. First, it employs a robust frequency estimator to obtain the fundamental frequency of the interference. Second, a series of discrete-time oscillators are used to generate interference harmonics, where harmonic phase and amplitude are obtained using the recursive least squares (RLS) algorithm. Third, the estimated interference harmonics are removed without distorting the neural signals at the interference frequencies. The simple structure and adequate numerical behavior of the algorithm renders it suitable for realtime implementation. Extensive experiments based on both invivo and synthesized data have been performed, where a reliable performance has been observed.
本文提出了一种用于去除神经记录实验中电力线干扰的算法。该算法不需要任何干扰参考信号,并且能够可靠地跟踪干扰在频率、相位和幅度上的变化。该方法包括三个主要步骤。首先,使用一种稳健的频率估计器来获取干扰的基频。其次,使用一系列离散时间振荡器来生成干扰谐波,其中谐波的相位和幅度通过递归最小二乘(RLS)算法获得。第三,去除估计出的干扰谐波,同时不使干扰频率处的神经信号失真。该算法结构简单且具有良好的数值特性,适合实时实现。基于体内和合成数据都进行了大量实验,实验结果表明该算法性能可靠。