Machine Learning for Healthcare Applications. Группа авторов

An EEG based approach. J. Adv. Manage. Sci., 1, 1, 61–65, 2013.

      12. Murugappan, M., Murugappan, S., Gerard, C., Wireless EEG signals based neuromarketing system using Fast Fourier Transform (FFT). 2014 IEEE 10th International Colloquium on Signal Processing and its Applications, IEEE, pp. 25–30, 2014.

      13. Boksem, M.A. and Smidts, A., Brain responses to movie trailers predict individual preferences for movies and their population-wide commercial success. J. Marketing Res., 52, 4, 482–492, 2015.

      14. Soleymani, M., Chanel, G., Kierkels, J.J., Pun, T., Affective ranking of movie scenes using physiological signals and content analysis. Proceedings of the 2nd ACM workshop on Multimedia semantics, pp. 32–39, 2008.

      15. Kawasaki, M. and Yamaguchi, Y., Effects of subjective preference of colors on attention-related occipital theta oscillations. NeuroImage, 59, 1, 808–814, 2012.

      16. Khushaba, R.N., Wise, C., Kodagoda, S., Louviere, J., Kahn, B.E., Townsend, C., Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking. Expert Syst. Appl., 40, 9, 3803–3812, 2013.

      17. Stickel, C., Fink, J., Holzinger, A., Enhancing universal access–EEG based learnability assessment. International Conference on Universal Access in Human–Computer Interaction, Springer, Berlin, Heidelberg, pp. 813–822, 2007.

      18. Holzinger, A., Scherer, R., Seeber, M., Wagner, J., Müller-Putz, G., Computational sensemaking on examples of knowledge discovery from neuroscience data: Towards enhancing stroke rehabilitation. International Conference on Information Technology in Bio- and Medical Informatics, Springer, Berlin, Heidelberg, pp. 166–168, 2012.

      19. Holzinger, A., Stocker, C., Bruschi, M., Auinger, A., Silva, H., Gamboa, H., Fred, A., On applying approximate entropy to ECG signals for knowledge discovery on the example of big sensor data. International Conference on Active Media Technology, Springer, Berlin, Heidelberg, pp. 646–657, 2012.

      20. Hargittai, S., Savitzky–Golay least-squares polynomial filters in ECG signal processing. Comput. Cardiol., 2005, 763–766, IEEE, 2005.

      21. Gandhi, V., Prasad, G., Coyle, D., Behera, L., McGinnity, T.M., Quantum neural network-based EEG filtering for a brain–computer interface. IEEE Trans. Neural Networks Learn. Syst., 25, 2, 278–288, 2013.

22. Abd Rahman, F. and Othman, M.F., Real time eye blink artifacts removal in electroencephalogram using Savitzky–Golay referenced adaptive filtering. International Conference for Innovation in Biomedical Engineering and Life Sciences, Springer, Singapore, pp. 68–71, 2015.

      23. Awal, M.A., Mostafa, S.S., Ahmad, M., Performance analysis of Savitzky–Golay smoothing filter using ECG signal. Int. J. Comput. Inf. Technol., 1, 02, 24–29, 2011.

      24. Kaur, B., Singh, D., Roy, P.P., A novel framework of EEG-based user identification by analyzing music-listening behavior. Multimedia Tools Appl., 76, 24, 25581–25602, 2017.

      ^*Corresponding author: [email protected]