Design of Wearable EEG Device for Seizures Early Detection

• Autorzy: Gaidar Viktoriia , Sudakov Oleksandr

Identyfikatory

DOI

10.24425/ijet.2021.135963

• Języki publikacji: EN

Abstrakty

EN

This paper presents the design of a wearable electroencephalography device and signal processing algorithm for early detection and forecasting of the epileptiform activity. The availability of the examination of functional brain activity for a prolonged period, outside of the hospital facilities, can provide new advantages in early diagnosis and intervention systems. In this study, the low-cost five-channel device is presented. The system consists of two main parts: the data acquisition and transmission units and processing algorithms. In order to create the robust epileptiform pattern recognition approach the application of statistical sampling and signal processing techniques are performed. The discrete wavelet and Hilbert-Huang transforms with principal component analysis are used in order to extract and select a low-dimension feature vector.

Słowa kluczowe

EN

circuit design; statistical sampling; Hilbert-Huang transform; feature selection

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2021
• Tom: Vol. 67, No. 2
• Strony: 187--192
• Opis fizyczny: Bibliogr. 15 poz., fot., schem., wykr.

Twórcy

autor

Gaidar Viktoriia

• Taras Shevchenko National University of Kyiv, Ukraine

autor

Sudakov Oleksandr

• Taras Shevchenko National University of Kyiv, Ukraine

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).