EEG spectro-temporal modulation energy: A new feature for automated diagnosis of Alzheimer's disease

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2011, Pages 3828-3831

  Trambaiolli, Lucas R ^a   Falk, Tiago H ^b   Fraga, Francisco J ^a   Anghinah, Renato ^c   Lorena, Ana C ^a  

^a UNIVERSIDADE FEDERAL DO ABC   (Brazil)

^b INRS EMT   (Canada)

^c UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

ALZHEIMER'S DISEASE; AMPLITUDE ENVELOPE; AMYLOID DEPOSITION; AUTOMATED DIAGNOSIS; BIPOLAR SIGNAL; BRAIN ACTIVITY; CLASSIFICATION AND REGRESSION TREE; DIAGNOSTICS TOOLS; EEG SIGNALS; ENERGY FEATURE; FULL BAND; HILBERT TRANSFORMATIONS; LOGISTIC REGRESSIONS; MULTI-CHANNEL; NEURAL NETWORK CLASSIFIER; SALIENT FEATURES; SUB-BAND MODULATION; SUB-BANDS;

BRAIN; ELECTROPHYSIOLOGY; MODULATION; NEURAL NETWORKS; NEURODEGENERATIVE DISEASES;

DIAGNOSIS;

AGED; ALZHEIMER DISEASE; ARTICLE; AUTOMATION; ELECTROENCEPHALOGRAPHY; HUMAN; MALE; METHODOLOGY; MIDDLE AGED; SIGNAL PROCESSING;

AGED; ALZHEIMER DISEASE; AUTOMATION; ELECTROENCEPHALOGRAPHY; HUMANS; MALE; MIDDLE AGED; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84055217869     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2011.6090951     Document Type: Conference Paper

References (20)

1. Alzheimer Association, "Alzheimer's disease facts and figures: 2010 report," Alzheimers Dement, vol. 6, no. 2, pp. 158-194, 2010.
2. B. Leifer, "Early diagnosis of Alzheimer's disease: clinical and economic benefits," J Am Geriatr Soc, vol. 51, pp. 281-288, 2003.
3. D. Parikh et al., "Ensemble-based data fusion for early diagnosis of Alzheimers disease," Proc Intl Conf IEEE-EMBS, pp. 2479-2482, 2005.
4. Z. Sankari, H. Adeli, and A. Adeli, "Intrahemispheric, interhemispheric, and distal EEG coherence in Alzheimers disease," Clin Neurophysiol, 2010, in press, doi:10.1016/j.clinph.2010.09.008.
5. H. Adeli, S. Ghosh-Dastidar, and N. Dadmehr, "Alzheimer's disease: models of computation and analysis of EEGs," Clin EEG Neurosci, vol. 36, no. 3, pp. 131-140, 2005.
6. J. Jeong, "EEG dynamics in patients with Alzheimer's disease," Clin Neurophysiol, vol. 115, no. 7, pp. 1490-1505, 2004.
7. A. Laxton et al., "A phase I trial of deep brain stimulation of memory circuits in Alzheimer's disease," Ann Neurol, vol. 68, no. 4, pp. 521-534, 2010.
8. G. McKhann, D. Drachman, M. Folstein, R. Katzman, D. Price, and E. Stadlan, "Clinical diagnosis of Alzheimer's disease: Report of the NINCDS-ADRDA Work Group," Neurology, vol. 34, no. 7, pp. 939-944, 1984.
9. R. Spitzer and J. Williams, User's guide for the structured clinical interview for DSM-III-R. American Psychiatric Publishing, Inc., 1990.
10. L. Trambaiolli, A. Lorena, F. Fraga, P. Kanda, R. Nitrini, and R. Anghinah, "Does EEG montage Influence Alzheimers Disease electroclinic diagnosis?" Int J Alzheimer's Disease, 2011, in press.
11. M. Le Van Quyen, J. Foucher, J. Lachaux, E. Rodriguez, A. Lutz, J. Martinerie, and F. Varela, "Comparison of Hilbert transform and wavelet methods for the analysis of neuronal synchrony," J Neurosci Meth, vol. 111, no. 2, pp. 83-98, 2001.
12. E. Frank, M. Hall, G. Holmes, R. Kirkby, B. Pfahringer, I. Witten, and L. Trigg, Data Mining and Knowledge Discovery Handbook. Springer, 2010, ch. Weka-a machine learning workbench for data mining, pp. 1269-1277.
13. C. Lehmann et al., "Application and comparison of classification of alzheimers disease in electrical brain activity (eeg)," J Neurosci Meth, vol. 161, pp. 342-350, 2007.
14. F. Duffy, M. Albert, G. McAnulty, and A. Garvey, "Age-related differences in brain electrical activity of healthy subjects," Annals of neurology, vol. 16, no. 4, pp. 430-438, 1984.
15. C. Babiloni, G. Binetti, A. Cassarino, G. Dal Forno, C. Del Percio, F. Ferreri, et al., "Sources of cortical rhythms in adults during physiological aging: a multicentric EEG study," Hum Brain Map, vol. 27, no. 2, pp. 162-172, 2006.
16. H. Adeli, S. Ghosh-Dastidar, and N. Dadmehr, "A spatio-temporal wavelet-chaos methodology for EEG-based diagnosis of Alzheimer's disease," Neurosci lett, vol. 444, no. 2, pp. 190-194, 2008.
17. N. Axmacher, M. Henseler, O. Jensen, I. Weinreich, C. Elger, and J. Fell, "Cross-frequency coupling supports multi-item working memory in the human hippocampus," P Natl Acad Sci USA, vol. 107, no. 7, p. 3228, 2010.
18. P. Putman, J. van Peer, I. Maimari, and S. van der Werff, "EEG theta/beta ratio in relation to fear-modulated response-inhibition, attentional control, and affective traits," Biol Psychol, vol. 83, no. 2, pp. 73-78, 2010.
19. L. Trambaiolli, A. Lorena, F. Fraga, and R. Anghinah, "Support Vector Machines in the Diagnosis of Alzheimer's Disease," in Proc ISSNIP Biosignals and Biorobotics Conf., vol. 1, 2010, pp. 1-6.
20. C. Melissant, A. Ypma, E. Frietman, and C. Stam, "A method for detection of Alzheimers disease using ICA-enhanced EEG measurements," Artif Intel Med, vol. 33, no. 3, pp. 209-222, 2005.