Please use this identifier to cite or link to this item: https://doi.org/10.1109/BMEI.2012.6513197
Title: Analysis and processing of in-vivo neural signal for artifact detection and removal
Authors: Islam, M.K.
Tuan, N.A.
Zhou, Y.
Yang, Z. 
Keywords: artifact characterization
artifact detection
artifact removal
artifact spectra
in-vivo neural recording
NEO
SDR improvement
Issue Date: 2012
Source: Islam, M.K.,Tuan, N.A.,Zhou, Y.,Yang, Z. (2012). Analysis and processing of in-vivo neural signal for artifact detection and removal. 2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012 : 437-442. ScholarBank@NUS Repository. https://doi.org/10.1109/BMEI.2012.6513197
Abstract: This paper analyses different types of artifacts that appear in neural recording experiments and thus a method is proposed to detect and remove artifacts as a part of preprocessing procedures before information decoding. Through modeling and data analysis, we reason that artifacts have different spectrum statistics compared with field potentials and spikes and the frequency bands of 150-400 Hz and >5 kHz are the most prospective regions to detect artifacts. A synthesized database based on recorded neural data and manually labeled artifacts has been built to allow quantitative evaluations of the proposed algorithm. Testing results have shown that over >80% positive detection ratio is achievable for artifacts with magnitude comparable to neural spikes. Quantitative signal-to-distortion ratio (SDR) simulation has shown that it is possible to have 10-30dB SDR improvement at waveform segments that contain artifacts. © 2012 IEEE.
Source Title: 2012 5th International Conference on Biomedical Engineering and Informatics, BMEI 2012
URI: http://scholarbank.nus.edu.sg/handle/10635/69388
ISBN: 9781467311816
DOI: 10.1109/BMEI.2012.6513197
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