Comparación del análisis espectral no paramétrico aplicado en las señales del EEG para identificar movimiento gestuales
DOI:
https://doi.org/10.61117/ipsumtec.v4i2.65Palabras clave:
Bioseñal delta, EEG, Métodos no paramétricos, Superficie PrefrontalResumen
Actualmente, se han aplicado técnicas de procesamiento digital en la determinación del parpadeo obtenida de señales del electroencefalograma (EEG). Sin embargo, no se ha propuesto una comparación determinista en la búsqueda de frecuencias dominantes que determinen los movimientos gestuales.
El propósito del siguiente estudio es determinar patrones generados por 6 movimientos gestuales: Apertura / Cierre - Ojo, Apertura / Cierre - Boca, Concentración, Meditación, Movimiento Ocular Arriba / Abajo y Movimiento Ojo Izquierdo / Derecho registrados en el
área prefrontal en el punto
Descargas
Métricas
Citas
A. P. Liavas, G. V. Moustakides, G. Henning, E. Z. Psarakis, y P. Husar. (1998). «A periodogram - based method for the detection of steady - state visually evoked potentials», IEEE Trans. Biomed. Eng., vol. 45, n.o 2, pp. 242-248, doi: 10.1109/10.661272.
Cong, F., Lin, Q. -H., Kuang, L. -D., Gong, X. -F., Astikainen, P., & Ristaniemi, T. (2015). Tensor decomposition of EEG signals: A brief review. Journal of Neuroscience Methods, vol. 248, pp. 59-69, doi: 10.1016/j.jneumeth.2015.03.018. DOI: https://doi.org/10.1016/j.jneumeth.2015.03.018
Dissanyaka, C., Cvetkovic, D., Abdullah, H., Ahmed, B., & Penzel, T. (2016). Classification of healthy and insomnia subjects based on wake - to - sleep transition, en IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), pp. 480-483, doi: 10.1109/IECBES.2016.7843497. DOI: https://doi.org/10.1109/IECBES.2016.7843497
Isaksson, A., Wennberg, A., & Zetterberg, L. H. (1981). Computer analysis of EEG signals with parametric models. Proc. IEEE, vol. 69, n. o4, pp. 451-461, doi: 10.1109/PROC.1981.11988. DOI: https://doi.org/10.1109/PROC.1981.11988
Jadhav, P. N., Shanamugan, D., Chourasia, A., Ghole, A. R., Acharyya, A., & Naik, G. (2014). Automated detection and correction of eye blink and muscular arte facts in EEG signal for analysis of Autism Spectrum Disorder. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. IEEEEng. Med. Biol. Soc. Annu. Int. Conf., vol. 2014, pp. 1881-1884, doi: 10.1109/EMBC.2014.6943977. DOI: https://doi.org/10.1109/EMBC.2014.6943977
Kam, J. W. Y., Griffin, S., Shen, A., Patel, S., Hinrichs, H., Heinze, H. -J., Deouell, L. Y., & Knight, R. T. (2019). Systematic comparison between a wireless EEG system with dry electrodes and a wired EEG system with wet electrodes. NeuroImage, vol. 184, pp. 119-129, doi: 10.1016/j.neuroimage.2018.09.012. DOI: https://doi.org/10.1016/j.neuroimage.2018.09.012
Li, Y., Lei, M. -Y., Guo, Y., Hu, Z., & Wei, H. -L. (2018). Time - Varying Nonlinear Causality Detection Using Regularized Orthogonal Least Squares and Multi - Wavelets With Applications to EEG. IEEE Access, vol.6, nºDOI: 10.1109/ACCESS.2018.2818789, pp.17826–1840. DOI: https://doi.org/10.1109/ACCESS.2018.2818789
Li, Yang, Lei, M., Cui, W., Guo, Y., & Wei, H. -L. (2019). A Parametric Time - Frequency Conditional Granger Causality Method Using Ultra - Regularized Orthogonal Least Squares and Multi wavelets for Dynamic Connectivity Analysis in EEGs. IEEE Trans. Biomed. Eng., vol.66, n.o12, pp.3509-3525, doi: 10.1109/TBME.2019.2906688. DOI: https://doi.org/10.1109/TBME.2019.2906688
Liavas, A. P., Moustakides, G. V., Henning, G., Psarakis, E. Z., & Husar, P. (1998). A periodogram - based method for the detection of steady - state visually evoked potentials. IEEE Trans. Biomed. Eng., vol. 45, n. o2, pp. 242-248, doi: 10.1109/10.661272. DOI: https://doi.org/10.1109/10.661272
Moreno Escobar, J. J., Morales Matamoros, O., Aguilar del Villar, E. Y., Tejeida Padilla, R., Lina Reyes, I., Espinoza Zambrano, B., Luna Gómez, B. D., & Calderón Morfín, V. H. (2021). Non - Parametric Evaluation Methods of the Brain Activity of a Bottlenose Dolphin during an Assisted Therapy. Animals, vol. 11, n.o2, doi: 10.3390/ani11020417. DOI: https://doi.org/10.3390/ani11020417
Murugappan, M., & Murugappan, S. (2013). Human emotion recognition through short time Electroencephalogram (EEG) signals using Fast Fourier Transform (FFT). En IEEE 9th International Colloquium on Signal Processing and its Applications, pp. 289-294, doi: 10.1109/CSPA.2013.6530058. DOI: https://doi.org/10.1109/CSPA.2013.6530058
Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998). A nonparametric method for automatic correction of intensity nonuniformity in MR Idata. IEEE Trans. Med. Imaging, vol. 17, n. o1, pp. 87-97, doi: 10.1109/42.668698. DOI: https://doi.org/10.1109/42.668698
Srinath, R., & Gayathri, R. (2020). Detection and classification of electroencephalogram signals for epilepsy disease using machine learning methods. Int. J. Imaging Syst. Technol., doi: https://doi.org/10.1002/ima.22486. DOI: https://doi.org/10.1002/ima.22486
Tseng, S. Y., Chen, R. -C., Chong, F. -C., & Kuo, T. -S. (1995). Evaluation of parametric methods in EEG signal analysis. Med. Eng. Phys., vol. 17, n.o 1, pp. 71-78, doi: 10.1016/1350-4533(95)90380-T. DOI: https://doi.org/10.1016/1350-4533(95)90380-T
Upadhyay, R., Kankar, P. K., Padhy, P. K., & Gupta, V. K. (2012). Extraction and classification of Electroencephalogram signals. 2012 IEEE International Conference on Computational Intelligence and Computing Research, pp.1-4, https://doi.org/10.1109/ICCIC.2012.6510216. DOI: https://doi.org/10.1109/ICCIC.2012.6510216
Vyas, A., Mishra, G., Tiwari, S., Upadhyay, R., & Padhy, P. K. (2013). Classification of two mental states using Electroencephalogram signals. En International Conference on Control, Automation, Robotics and Embedded Systems (CARE), pp.1-4, doi: 10.1109/CARE.2013.6733769. DOI: https://doi.org/10.1109/CARE.2013.6733769
Zhouyan Feng & Zheng Xu. (2002). Analysis of rat electroencephalogram under slow wave sleep using wavelet transform. En Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology, vol. 1, pp. 94-95, vol.1, doi: 10.1109/IEMBS.2002.1134404. DOI: https://doi.org/10.1109/IEMBS.2002.1134404
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2021 José de Jesús Moreno Vázquez, Brayan Quino Ortiz y Aldo Rafael Sartorius Castellanos
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
