J Med Syst - The effect of multiscale PCA de-noising in epileptic seizure detection.

Tópicos

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Resumo

In this paper we describe the effect of Multiscale Principal Component Analysis (MSPCA) de-noising method in terms of epileptic seizure detection. In addition, we developed a patient-independent seizure detection algorithm using Freiburg EEG database. Each patient contains datasets called "ictal" and "interictal". Window length of 16 s was applied to extract EEG segments from datasets of each patient. Furthermore, Power Spectral Density (PSD) of each EEG segment was estimated using different spectral analysis methods. Afterwards, these values were fed as input to different machine learning methods that were responsible for seizure detection. We also applied MSPCA de-noising method to EEG segments prior to PSD estimation to determine if MSPCA can further enhance the classifiers' performance. The MSPCA drastically improved both the sensitivity and the specificity, increasing the overall accuracy of all three classifiers up to 20%. The best overall detection accuracy (99.59%) was achieved when Eigenvector analysis was used for frequency estimation, and C4.5 as a classifier. The experiment results show that MSPCA is an effective de-noising method for improving the classification performance in epileptic seizure detection.

Resumo Limpo

paper describ effect multiscal princip compon analysi mspca denois method term epilept seizur detect addit develop patientindepend seizur detect algorithm use freiburg eeg databas patient contain dataset call ictal interict window length s appli extract eeg segment dataset patient furthermor power spectral densiti psd eeg segment estim use differ spectral analysi method afterward valu fed input differ machin learn method respons seizur detect also appli mspca denois method eeg segment prior psd estim determin mspca can enhanc classifi perform mspca drastic improv sensit specif increas overal accuraci three classifi best overal detect accuraci achiev eigenvector analysi use frequenc estim c classifi experi result show mspca effect denois method improv classif perform epilept seizur detect

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