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Implementation of Low-Pass Fractional Filtering for the Purpose of Analysis of Electroencephalographic Signals

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Non-Integer Order Calculus and its Applications (RRNR 2017)

Abstract

Implementation of fractional order filters is still a novel, but promising area in the signal processing – in particular in analysis of bio-medical data, such as inter alia electroencephalography (EEG), where may occur large signal distortion. One of the main challenges is the complexity of the EEG data. In this paper potential application of various low-pass fractional filters (Bi-Fractional Filtering) applied for the purpose of electroencephalography (EEG) analysis was presented. The authors of this paper tested two types (0.0013th and 0.13th orders) of non-integer, low-pass filters. The results give promising results and were compared with typical low-pass 13 Hz Butterworth filter (4th Order).

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Acknowledgment

Work realised in the scope of project titled “Design and application of non-integer order subsystems in control systems”. Project was financed by National Science Centre on the base of decision no. DEC-2013/09/D/ST7/03960.

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Correspondence to Aleksandra Kawala-Janik .

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Kawala-Janik, A. et al. (2019). Implementation of Low-Pass Fractional Filtering for the Purpose of Analysis of Electroencephalographic Signals. In: Ostalczyk, P., Sankowski, D., Nowakowski, J. (eds) Non-Integer Order Calculus and its Applications. RRNR 2017. Lecture Notes in Electrical Engineering, vol 496. Springer, Cham. https://doi.org/10.1007/978-3-319-78458-8_6

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  • DOI: https://doi.org/10.1007/978-3-319-78458-8_6

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