Authors: Pitchaipillai Prema; T. Kesavamurthy; P. Arulmozhivarman
Addresses: Department of Biomedical Engineering, PSG College of Technology, Coimbatore, Tamil Nadu, India ' Department of Electronics and Communication Engineering, PSG College of Technology, Coimbatore, Tamil Nadu, India ' School of Electrical Engineering, VIT University, Vellore, Tamil Nadu, India
Abstract: P300 is an endogenous event related potential (ERP) elicited by a rare or significant visual stimulus and is widely preferred in brain computer interface (BCI) to assess the cognition level of the subject. Many researchers contribute to P300 estimation as this signal is of very low strength in background electroencephalogram (EEG) activity. This paper proposes a novel signal processing algorithm to detect the P300 event in a single trial EEG acquired from midline electrode sites in oddball paradigm to evaluate attention and memory related tasks of subjects. The algorithm incorporates wavelet combined adaptive noise canceller followed by ensemble and moving averager. Time domain analysis shows the localisation of ERP around 300 ms for target stimuli attended by the subjects. The short-time Fourier transform (STFT) analysis shows strong theta activity associated to memory related task. Thus, the proposed algorithm is efficient in detecting the P300 with higher correlation coefficient of 0.82 (average) compared to other existing methods.
Keywords: brain computer interface; BCI; P300-event related potential; attention; adaptive filter; ensemble averaging; moving averager; latency; SNR; short-time Fourier transform; STFT; time-domain; frequency-domain.
International Journal of Biomedical Engineering and Technology, 2021 Vol.36 No.4, pp.358 - 374
Received: 29 Jan 2018
Accepted: 17 May 2018
Published online: 02 Aug 2021 *