Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10439-010-0201-5
Title: 1/f neural noise reduction and spike feature extraction using a subset of informative samples
Authors: Yang, Z. 
Hoang, L.
Zhao, Q.
Keefer, E.
Liu, W.
Keywords: Action potential
Clustering
Spike feature extraction
Spike sorting
Issue Date: Apr-2011
Citation: Yang, Z., Hoang, L., Zhao, Q., Keefer, E., Liu, W. (2011-04). 1/f neural noise reduction and spike feature extraction using a subset of informative samples. Annals of Biomedical Engineering 39 (4) : 1264-1277. ScholarBank@NUS Repository. https://doi.org/10.1007/s10439-010-0201-5
Abstract: This article describes a study on neural noise and neural signal feature extraction, targeting real-time spike sorting with miniaturized microchip implementation. Neuronal signature, noise shaping, and adaptive bandpass filtering are reported as the techniques to enhance the signal-to-noise ratio (SNR). A subset of informative samples of the waveforms is extracted as features for classification. Quantitative and comparative experiments with both synthesized and animal data are included to evaluate different feature extraction approaches. In addition, a preliminary hardware implementation has been realized using an integrated circuit. © 2010 Biomedical Engineering Society.
Source Title: Annals of Biomedical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/53844
ISSN: 00906964
DOI: 10.1007/s10439-010-0201-5
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