Abstract
EEG signal analysis is commonly used by skilled neurologists as a useful tool in the diagnosis of specific neurological dysfunction. To greatly facilitate the diagnostic process and improve the efficiency of decision making decision support systems are developed based on expert knowledge. This paper presents the design of a computer system supporting seizure detection, based on real EEG records. The system is based on modern signal processing tools that allow for time-frequency representation of the analyzed signal. The proposed solution should be treated as a decision support computer system. The system has been designed to facilitate the rapid detection of characteristic graphoelements to effectively detect epileptic seizures. The proposed solution can have a significant impact on an accuracy and speed in the analysis of EEG signals, which may significantly shorten the time of making diagnosis trials. The proposed system is based on studies using real EEG records of patients with epilepsy as well as healthy subjects prepared in collaboration with the medical staff of the Ward of Neurology and Strokes of the Provincial Hospital of Zielona Góra, Poland.
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Rutkowski, G., Patan, K. (2014). Computer-Aided Off-Line Diagnosis of Epileptic Seizures. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8468. Springer, Cham. https://doi.org/10.1007/978-3-319-07176-3_17
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DOI: https://doi.org/10.1007/978-3-319-07176-3_17
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