Performance comparison of seizure detection methods using EEG of newborns for implementation of a DSP subsystem

Mostefa Mesbah*, Boualem Boashash

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةمراجعة النظراء

2 اقتباسات (Scopus)

ملخص

This paper deals with the problem of seizure detection in newborns using the EEG signal. The performance of three techniques for seizure detection is investigated. The technique of Roessgen is model based and uses parameter estimation for detection. The two other methods are non-parametric. The technique of Gotman uses frequency analysis to determine the changes in the dominant peak of the frequency spectrum of short epochs of EEG data. The technique of Liu performs analysis in the time domain and is based on the auto-correlation function of short epochs of EEG data. This paper discusses the underlying methodology of the different techniques and presents a comparison of their performance on simulated EEG signal with the aim of considering the best for a possible implementation within a DSP system for automatic seizure detection. The obtained results show that Gotman's method outperforms the two other methods in terms of good detection, the missing detection, and the false alarm rates.

اللغة الأصليةEnglish
الصفحات (من إلى)IV/3860-IV/3863
دوريةICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
مستوى الصوت4
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2002
منشور خارجيًانعم
الحدث2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL
المدة: مايو ١٣ ٢٠٠٢مايو ١٧ ٢٠٠٢

ASJC Scopus subject areas

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