Automatic detection of photic evoked spikes contaminated with slow burst by use of morphological filter and similarity coefficient

Author

Nishida, Shigeto ; Sugi, Takenao ; Ikeda, Akio ; Nagamine, Takashi ; Shibasaki, Hiroshi ; Nakamura, Masatoshi

Author_Institution

Dept. of Comput. & Commun. Eng., Fukuoka Inst. of Technol., Fukuoka, Japan

fYear

2012

fDate

1-4 July 2012

Firstpage

159

Lastpage

164

Abstract

A method for detecting spikes and slow burst in photic evoked electroencephalogram (EEG) was proposed. The spikes were detected by combining methods of the morphological filter and the similarity coefficient in the time domain. The slow burst was detected by using pole of AR model (auto-regressive model) in the frequency domain. The proposed method was applied for the photic evoked EEG data containing spikes and slow burst, and brought satisfactory coincidence with the results interpreted by a qualified electroencephalographer.

Keywords

autoregressive processes; electroencephalography; neurophysiology; physiological models; AR model; automatic detection; autoregressive model; frequency domain; morphological filter; photic evoked EEG data; photic evoked electroencephalogram; photic evoked spikes; slow burst; spike detection method; Brain modeling; Electroencephalography; Frequency domain analysis; Morphological filter; Similarity coefficient; Slow burst detection; Spike detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Complex Medical Engineering (CME), 2012 ICME International Conference on

Conference_Location

Kobe

Print_ISBN

978-1-4673-1617-0

Type

conf

DOI

10.1109/ICCME.2012.6275684

Filename

6275684