TY - GEN
T1 - Classification of Alzheimer's disease and mild cognitive impairment by pattern recognition of EEG power and coherence
AU - Akrofi, Kwaku
AU - Pal, Ranadip
AU - Baker, Mary C.
AU - Nutter, Brian S.
AU - Schiffer, Randolph W.
PY - 2010
Y1 - 2010
N2 - This paper describes a methodology used to classify Alzheimer's disease (AD) and mild cognitive impairment (MCI) with high accuracy using EEG data. The sequential forward floating search (SFFS) was used to select features from relative average power for channel locations in frequency bands delta, theta, alpha, and beta, and coherence between intrahemispheric channel pairs for the same frequency ranges. The selected feature sets allowed us to achieve close to 90% classifier accuracy when classifying MCI patients and normal subjects. Our results showed that selecting features from a combined set of power and coherence features produced better results than the use of either feature independently. The combined feature set also showed better classification rates than a Bayesian classifier fusion approach.
AB - This paper describes a methodology used to classify Alzheimer's disease (AD) and mild cognitive impairment (MCI) with high accuracy using EEG data. The sequential forward floating search (SFFS) was used to select features from relative average power for channel locations in frequency bands delta, theta, alpha, and beta, and coherence between intrahemispheric channel pairs for the same frequency ranges. The selected feature sets allowed us to achieve close to 90% classifier accuracy when classifying MCI patients and normal subjects. Our results showed that selecting features from a combined set of power and coherence features produced better results than the use of either feature independently. The combined feature set also showed better classification rates than a Bayesian classifier fusion approach.
KW - Alzheimer's disease (AD)
KW - Bayesian data fusion
KW - Mild cognitive impairment (MCI)
KW - Sequential floating forward search (SFFS)
UR - http://www.scopus.com/inward/record.url?scp=78049397115&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2010.5495193
DO - 10.1109/ICASSP.2010.5495193
M3 - Conference contribution
AN - SCOPUS:78049397115
SN - 9781424442966
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 606
EP - 609
BT - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Y2 - 14 March 2010 through 19 March 2010
ER -