Title :
Analysis and processing of in-vivo neural signal for artifact detection and removal
Author :
Islam, Md. Kamrul ; Tuan, Nguyen Anh ; Yin Zhou ; Zhi Yang
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
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.
Keywords :
bioelectric phenomena; data analysis; medical signal processing; neurophysiology; SDR; artifact detection; artifact removal; data analysis; frequency 150 Hz to 400 Hz; in-vivo neural signal analysis; in-vivo neural signal processing; information decoding; neural data; neural recording; neural spikes; signal-to-distortion ratio simulation; spectrum statistics; waveform segments; NEO; SDR improvement; artifact characterization; artifact detection; artifact removal; artifact spectra; in-vivo neural recording;
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-1183-0
DOI :
10.1109/BMEI.2012.6513197