Abstract
Autonomic control evidenced in both heart rate variability (HRV) and electroencephalographic (EEG) oscillations, reflect the behaviour of the underlying physiological non-stationary dynamical systems. In order to assess the influence of autonomic changes in the performance of an asynchronous brain-computer interface, recurrence analysis of EEG spectral density time series and HRV feature sets were used in binary classifiers to detect rest state from mental calculation state. Results suggest that recurrence indices of HRV might contribute to improve activity episodes detection for BCI control as the highest performance was achieved with power spectral density features of EEG in combination with recurrence HRV features (AUROC \(=0.81\pm 0.07\)).
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References
Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Peng, C.-K., Moody, G.B., Eugene Stanley, H.: Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals. Circulation 101(23), e215–e220 (2000)
Marwan, N.: Cross Recurrence Plot Toolbox for Matlab. Potsdam Institute for Climate Impact Research (PIK), October 2016
Marwan, N., Carmenromano, M., Thiel, M., Kurths, J.: Recurrence plots for the analysis of complex systems. Phys. Rep. 438(5–6), 237–329 (2007)
Schlenker, J., Socha, V., Riedlbauchová, L., Nedělka, T., Schlenker, A., Potočková, V., Malá, Š., Kutílek, P.: Recurrence plot of heart rate variability signal in patients with vasovagal syncopes. Biomed. Signal Process. Control 25, 1–11 (2016)
Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-computer interfaces for communication and control. Clin. Neurophysiol.: Official J. Int. Fed. Clin. Neurophysiol. 113, 767–791 (2002)
Zyma, I., Tukaev, S., Seleznov, I., Kiyono, K., Popov, A., Chernykh, M., Shpenkov, O.: Electroencephalograms during mental arithmetic task performance. Data 4(1), 14 (2019)
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This work is supported by Dirección de Investigación of Universidad Iberoamericana Ciudad de México (DINV), under research project on BCI.
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Ledesma-Ramírez, C.I., Bojorges-Valdez, E., Yanez-Suarez, O., Piña-Ramírez, O. (2020). Recurrence Analysis of EEG Power and HRV Time Series for Asynchronous BCI Control. In: González Díaz, C., et al. VIII Latin American Conference on Biomedical Engineering and XLII National Conference on Biomedical Engineering. CLAIB 2019. IFMBE Proceedings, vol 75. Springer, Cham. https://doi.org/10.1007/978-3-030-30648-9_27
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DOI: https://doi.org/10.1007/978-3-030-30648-9_27
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