DocumentCode :
2116457
Title :
Two level PCA to reduce noise and EEG from evoked potential signals
Author :
Palaniappan, Ramaswamy ; Anandan, S. ; Raveendran, P.
Author_Institution :
Fac. of Inf. Sci. & Technol., Multimedia Univ., Malaysia
Volume :
3
fYear :
2002
fDate :
2-5 Dec. 2002
Firstpage :
1688
Abstract :
Two common artifacts that corrupt evoked responses are noise and background electroencephalogram (EEG). In this paper, a two-level principal component analysis (PCA) is used to reduce these artifacts from single trial evoked responses. The first level PCA is applied to reduce noise from these VEP signals while the second level PCA reduces EEG. The method is used to analyse the object recognition and decision-making capability during visual responses. The analysis is extended to study the differences in visual response between alcoholics and non-alcoholics using single trial P3 visual evoked potential (VEP) signals. The analysis shows that alcoholics respond slower and weaker to visual stimulus as compared to non-alcoholics.
Keywords :
electroencephalography; neurophysiology; noise; object recognition; principal component analysis; visual evoked potentials; EEG; PCA; alcoholics; decision making capability; noise reduction; object recognition; two level principal component analysis; visual evoked potential; visual response; visual stimulus; Acoustic noise; Alcoholic beverages; Alcoholism; Electrodes; Electroencephalography; Noise level; Noise reduction; Object recognition; Principal component analysis; Signal analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation, Robotics and Vision, 2002. ICARCV 2002. 7th International Conference on
Print_ISBN :
981-04-8364-3
Type :
conf
DOI :
10.1109/ICARCV.2002.1235029
Filename :
1235029
Link To Document :
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