Title :
Fast Extraction of Somatosensory Evoked Potential Using RLS Adaptive Filter Algorithms
Author :
Ren, Zhaoli ; Zou, Yuexian ; Zhang, Zhiguo ; Hu, Yong
Author_Institution :
Adv. Digital Signal Process. Lab., Peking Univ., Shenzhen, China
Abstract :
This paper evaluates the efficacy of the recursive least squares (RLS) in adaptive noise canceller (RLS-ANC) for fast extraction of somatosensory evoked potentials (SEPs). The RLSANC method was verified by simulation of electroencephalography (EEG) and Gaussian noise contaminated SEP signals at different signal-to-noise ratios (SNRs). RLS was found to converge faster than the least mean squares (LMS) algorithm in ANC, i.e. SEP extraction by RLS-ANC required fewer trials than LMS-ANC. Experimental results showed that RLS-ANC with less than 50 trials could provide similar performance in SEP extraction to those extracted by the conventional ensemble averaging with 500 trials even at SNR of 20 dB.
Keywords :
electroencephalography; filtering theory; least squares approximations; mechanoception; medical signal processing; neurophysiology; recursive estimation; signal denoising; EEG SEP signals; Gaussian noise contaminated SEP signals; RLS adaptive filter algorithms; RLSANC method; adaptive noise canceller; electroencephalography; somatosensory evoked potential fast extraction; the recursive least squares; Adaptive filters; Brain modeling; Electroencephalography; Filtering algorithms; Least squares approximation; Monitoring; Noise cancellation; Resonance light scattering; Signal processing algorithms; Signal to noise ratio;
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
DOI :
10.1109/CISP.2009.5304009
