DocumentCode
140092
Title
Comparison study of seizure detection using stationary and nonstationary methods
Author
Ying Li ; Yue-Loong Hsin ; Wentai Liu
Author_Institution
Bioeng. Dept., Univ. of California, Los Angeles, Los Angeles, CA, USA
fYear
2014
fDate
26-30 Aug. 2014
Firstpage
3272
Lastpage
3275
Abstract
We present an accurate seizure detection algorithm, and make a detailed comparison of two frequency analysis methods: a widely used stationary method - Fast Fourier Transform (FFT) and a relatively new nonstationary method - Hilbert-Huang Transform (HHT). Two public databases and one our own database were tested. The results show that our algorithm has very high accuracy compared with the state-of-the-art. More interestingly, it shows that the nonstationary method HHT offers better performance than the stationary method FFT in seizure detection. Therefore we propose that we should pay attention to the nonstationarity of EEG signal, since the “stationary assumption” may introduce some inaccuracy.
Keywords
Hilbert transforms; electroencephalography; fast Fourier transforms; frequency-domain analysis; medical disorders; medical signal detection; EEG signal nonstationarity; Fast Fourier Transform; Hilbert-Huang Transform; frequency analysis methods; nonstationary method HHT; public databases; seizure detection algorithm; stationary assumption; stationary method FFT; Accuracy; Classification algorithms; Databases; Electroencephalography; Feature extraction; Time-frequency analysis; Transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location
Chicago, IL
ISSN
1557-170X
Type
conf
DOI
10.1109/EMBC.2014.6944321
Filename
6944321
Link To Document