참고문헌
- Samaa S. Abdulwahab, "EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm", Iraqi Journal for Electrical and Electronic Engineering, Vol. 17, December 2021. DOI: 10.1088/1742-6596/1973/1/012056
- L. Bahatti1, A. El Magri1, A. Lekova2, O.Bouattane, "Developing Brain Computer Interface for Motor Imagery Mental Commands", ISSN 2603-4697 (Online) Complex Control Systems Vol. 2, No 1, 2020, pp. 1-6, pp.
- Sandeep Bodda, Shyam Diwakar, "Exploring EEG spectral and temporal dynamics underlying a hand grasp movement", PLoS One. 2022 Jun 23;17(6):e0270366., DOI: 10.1371/journal.pone.0270366
- J. Hurtado-Rincon, S. Rojas-Jaramillo, Y. Ricardo-Cespedes, A. M. A lvarez-Meza and G. Castellanos-Dominguez, "Motor imagery classification using feature relevance analysis: An Emotiv-based BCI system", 2014 XIX Symposium on Image, Signal Processing and Artificial Vision, Armenia, Colombia, 2014, pp. 1-5, DOI: 10.1109/STSIVA.2014.7010165
- Rodriguez-Bermudez G, Garcia-Laencina PJ. "Automatic and adaptive classification of electroencephalographic signals for brain computer interfaces". J Med Syst. 2012 Nov;36 Suppl 1:S51-63. DOI: 10.1007/s10916-012-9893-4. Epub 2012 Nov 2. PMID: 23117792.
- Reder, E.E., de Quadros Martins, A.R., Ferreira, V.R.T., Kalil, F. (2014). Neural Interface Emotiv EPOC and Arduino: Brain-Computer Interaction in a Proof of Concept. In: Kurosu, M. (eds) Human-Computer Interaction. Advanced Interaction Modalities and Techniques. HCI 2014. Lecture Notes in Computer Science, vol 8511. Springer, Cham. https://doi.org/10.1007/978-3-319-07230-2_58
- STRMISKA, Martin, Zuzana KOUDELKOVA a Martina ZABCIKOVA. "Measuring brain signals using emotiv devices". WSEAS Transactions on Systems and Control. 2018, vol. 13, s. 537-542. ISSN 1991-8763
- O. Carrera-Leon, J. M. Ramirez, V. Alarcon-Aquino, M. Baker, D. D'Croz-Baron and P. Gomez-Gil, "A motor imagery BCI experiment using wavelet analysis and spatial patterns feature extraction", 2012 Workshop on Engineering Applications, Bogota, Colombia, 2012, pp. 1-6, DOI: 10.1109/WEA.2012.6220084.
- Szczepan Paszkiel, "Brain-computer technology-based training system in the field of motor imagery", IET Science, Measurement & Technology 14, December 2020, DOI: 10.1049/iet-smt.2019.0522
- Ekansh Sareen, Anubha Gupta, "Studying functional brain networks from dry electrode EEG set during music and resting states in neurodevelopment disorder", http://dx.doi.org/10.1101/759738doi: posted online Sep. 8, 2019;
- V.Asanza, "SSVEP-EEG Signal classification based on Emotiv Epoc BCI and Raspberry PI", IFACT conference paper, 388 -393 pp., 2021, https://doi.org/10.1016/j.ifacol.2021.10.287
- Tat'y Mwata-Velu, Jose Ruiz-Pinales "Motor Imagery Classification Based on a Recurrent-Convolutional Architecture to Control a Hexapod Robot", Mathematics 2021, 9, 606. DOI: 10.3390/math9060606
- Marquos Zaki, Ali Alquraini, "Home Automation using EMOTIV: Controlling TV by Brainwaves", Journal of Ubiquitous Systems & Pervasive Networks Volume 10, No. 1 (2018) pp. 27-32, DOI: 10.5383/JUSPN.10.01.004
- Craik A, He Y, Contreras-Vidal JL. Deep learning for electroencephalogram (EEG) classification tasks: a review. J Neural Eng. 2019 Jun;16(3):031001. DOI: 10.1088/1741-2552/ab0ab5. Epub 2019 Feb 26. PMID: 30808014.
- Lujan, M.A.; Jimeno, M.V.; Mateo Sotos, J.; Ricarte, J.J.; Borja, A.L. "A Survey on EEG Signal Processing Techniques and Machine Learning: Applications to the Neurofeedback of Autobiographical Memory Deficits in Schizophrenia", Electronics 2021, 10, 3037. https://doi.org/10.3390/electronics10233037
- William O, "Handbook of EEG interpretation", 2008 Demos Medical Publishing, LLC, ISBN-10: 0826147089
- Shoorangiz, Reza, Stephen J. Weddell, and Richard D. Jones. "EEG-Based Machine Learning: Theory and Applications", Handbook of Neuroengineering. Singapore: Springer Singapore, 2021. 1-39, https://doi.org/10.1007/978-981-15-2848-4_70-1
- Toshihisa Tanaka and Mahnaz Arvaneh, "Signal Processing and Machine Learning for Brain--Machine Interfaces", The Institution of Engineering and Technology is registered as a Charity in England, 2018, ISBN: 9781785613982, DOI: 10.1049/PBCE114E