MÁY ĐO ĐIỆN NÃO ĐỒ (EEG) VÀ ĐỊNH HƯỚNG NGHIÊN CỨU VỀ LĨNH VỰC KHOA HỌC THẦN KINH
Nội dung chính của bài viết
Tóm tắt
Bài viết giới thiệu về máy đo điện não đồ (EEG) và các bước tiến hành một thí nghiệm đo điện não đồ. Các tính năng cũng như kết cấu kĩ thuật của máy được trình bày một cách chi tiết. Thông qua 9 bước thực hiện một thí nghiệm, có thể đưa ra định hướng một cách rõ ràng để người đọc tham khảo và thiết kế một thí nghiệm tương ứng. Các bước bảo trì máy sau khi hoàn thành thí nghiệm cũng được đề cập trong bài viết này để cung cấp cho người đọc cái nhìn tổng quát và ứng dụng khi sử dụng máy EEG thực hiện thí nghiệm. Như vậy, nền tảng ban đầu về việc tiến hành thí nghiệm, hoặc thực nghiệm các nghiên cứu về lĩnh vực khoa học thần kinh đang bắt đầu được quan tâm, đầu tư và phát triển tại Việt Nam.
Từ khóa
máy đo điện não đồ, khoa học thần kinh, kinh nghiệm thực tiễn, nghiên cứu khoa học
Chi tiết bài viết
Tài liệu tham khảo
Abhang, P. A., Gawali, B. W., & Mehrotra, S. C. (2016). Introduction to EEG-and speech-based emotion recognition. Academic Press.
Alix, J. J., Ponnusamy, A., Pilling, E., & Hart, A. R. (2017). An introduction to neonatal EEG. Paediatrics and Child Health, 27(3), 135-142.
Alwedaie, S. A., Khabbaz, H. A., Hadi, S. R., & Al-Hakim, R. (2018). EEG-based analysis for learning through virtual reality environment. Journal of Biosensors and Bioelectronics,
9(1), 249.
Amezcua-Gutiérrez, C., Hernández-González, M., Guasti, A. F., Aguilar, M. A. C., & Guevara, M. A. (2021). Observing Erotic Videos with Heterosexual Content Induces Different Cerebral Responses in Homosexual and Heterosexual Men. Journal of homosexuality, 68(1), 138-156.
Antonenko, P., Paas, F., Grabner, R., & Van Gog, T. (2010). Using electroencephalography to measure cognitive load. Educational Psychology Review, 22(4), 425-438.
Babiker, A., Faye, I., Mumtaz, W., Malik, A. S., & Sato, H. (2019). EEG in classroom: EMD features to detect situational interest of students during learning. Multimedia Tools and Applications, 78(12), 16261-16281.
Clarke, A. R., Barry, R. J., & Johnstone, S. (2020). Resting state EEG power research in attention-deficit/hyperactivity disorder: a review update. Clinical Neurophysiology, 131(7),
1463-1479.
Cooper, R., Osselton, J. W., & Shaw, J. C. (2014). EEG technology. Butterworth-Heinemann.
Davidson, R. J., Jackson, D. C. & Larson, C. L. (2000). Human electroencephalography. In: Cacioppo JT, Tassinary LG, Berntson GG, editors. Handbook of psychophysiology. 2. Cambridge, UK: Cambridge University Press.
Horat, S. K., Favre, G., Prévot, A., Ventura, J., Herrmann, F. R., Gothuey, I., ... & Missonnier, P. (2018). Impaired social cognition in schizophrenia during the Ultimatum Game: an EEG study. Schizophrenia research, 192, 308-316.
Huang, H., Xie, Q., Pan, J., He, Y., Wen, Z., Yu, R., & Li, Y. (2019). An EEG-based brain computer interface for emotion recognition and its application in patients with Disorder of Consciousness. IEEE Transactions on Affective Computing.
Ianof, J. N., & Anghinah, R. (2017). Traumatic brain injury: An EEG point of view. Dementia & neuropsychologia, 11(1), 3-5.
Ibanez, A., Melloni, M., Huepe, D., Helgiu, E., Rivera-Rei, A., Canales-Johnson, A., ... & Moya, A. (2012). What event-related potentials (ERPs) bring to social neuroscience?. Social neuroscience, 7(6), 632-649.
Liu, Y., Sourina, O., Liew, H. P., Salem, H. S., & Ang, E. (2017). Human factors evaluation in maritime virtual simulators using mobile EEG-based neuroimaging. Transdisciplinary Engineering: A Paradigm Shift, 5, 261-268.
Luck, S. J. (2005). An introduction to the event-related potential technique. MIT Press. Page 304 - Chapter 8.
Malik, A. S., & Amin, H. U. (2017). Designing EEG experiments for studying the brain: Design code and example datasets. Academic Press.
Nandi, A., Xhafa, F., Subirats, L., & Fort, S. (2021). Real-time emotion classification using eeg data stream in e-learning contexts. Sensors, 21(5), 1589.
Nidal, K., & Malik, A. S. (Eds.). (2014). EEG/ERP analysis: methods and applications. Crc Press.
Padfield, N., Zabalza, J., Zhao, H., Masero, V., & Ren, J. (2019). EEG-based brain-computer interfaces using motor-imagery: Techniques and challenges. Sensors, 19(6), 1423.
Price, J., & Budzynski, T. (2009). Anxiety, EEG patterns, and neurofeedback. Introduction to quantitative EEG and neurofeedback: Advanced theory and applications, 453-470.
Ramirez, R., & Vamvakousis, Z. (2012, December). Detecting emotion from EEG signals using the emotive epoc device. In International Conference on Brain Informatics (pp. 175-184). Springer, Berlin, Heidelberg.
Schneider, D., Zickerick, B., Thönes, S., & Wascher, E. (2020). Encoding, storage, and response preparation—Distinct EEG correlates of stimulus and action representations in working memory. Psychophysiology, 57(6), e13577.
Siuly, S., Li, Y., & Zhang, Y. (2016). EEG signal analysis and classification. IEEE Trans Neural Syst Rehabilit Eng, 11, 141-144.
Song, Z., Liu, C., Shi, R., Zhang, M., Wang, H., & Mei, Y. (2020). Neural activities during the evaluation of luxury goods-to-service brand extension: An event-related potentials (ERPs) study. Journal of Neuroscience, Psychology, and Economics, 13(3), 127.
Szurhaj, W., Lamblin, M. D., Kaminska, A., & Sediri, H. (2015). EEG guidelines in the diagnosis of brain death. Neurophysiologie Clinique/Clinical Neurophysiology, 45(1), 97-104.
Ünal, Ö., Özcan, Ö., Öner, Ö., Akcakin, M., Aysev, A., & Deda, G. (2009). EEG and MRI findings and their relation with intellectual disability in pervasive developmental disorders. World Journal of Pediatrics, 5(3), 196-200.
Yadava, M., Kumar, P., Saini, R., Roy, P. P., & Dogra, D. P. (2017). Analysis of EEG signals and its application to neuromarketing. Multimedia Tools and Applications, 76(18), 19087-19111.
Alix, J. J., Ponnusamy, A., Pilling, E., & Hart, A. R. (2017). An introduction to neonatal EEG. Paediatrics and Child Health, 27(3), 135-142.
Alwedaie, S. A., Khabbaz, H. A., Hadi, S. R., & Al-Hakim, R. (2018). EEG-based analysis for learning through virtual reality environment. Journal of Biosensors and Bioelectronics,
9(1), 249.
Amezcua-Gutiérrez, C., Hernández-González, M., Guasti, A. F., Aguilar, M. A. C., & Guevara, M. A. (2021). Observing Erotic Videos with Heterosexual Content Induces Different Cerebral Responses in Homosexual and Heterosexual Men. Journal of homosexuality, 68(1), 138-156.
Antonenko, P., Paas, F., Grabner, R., & Van Gog, T. (2010). Using electroencephalography to measure cognitive load. Educational Psychology Review, 22(4), 425-438.
Babiker, A., Faye, I., Mumtaz, W., Malik, A. S., & Sato, H. (2019). EEG in classroom: EMD features to detect situational interest of students during learning. Multimedia Tools and Applications, 78(12), 16261-16281.
Clarke, A. R., Barry, R. J., & Johnstone, S. (2020). Resting state EEG power research in attention-deficit/hyperactivity disorder: a review update. Clinical Neurophysiology, 131(7),
1463-1479.
Cooper, R., Osselton, J. W., & Shaw, J. C. (2014). EEG technology. Butterworth-Heinemann.
Davidson, R. J., Jackson, D. C. & Larson, C. L. (2000). Human electroencephalography. In: Cacioppo JT, Tassinary LG, Berntson GG, editors. Handbook of psychophysiology. 2. Cambridge, UK: Cambridge University Press.
Horat, S. K., Favre, G., Prévot, A., Ventura, J., Herrmann, F. R., Gothuey, I., ... & Missonnier, P. (2018). Impaired social cognition in schizophrenia during the Ultimatum Game: an EEG study. Schizophrenia research, 192, 308-316.
Huang, H., Xie, Q., Pan, J., He, Y., Wen, Z., Yu, R., & Li, Y. (2019). An EEG-based brain computer interface for emotion recognition and its application in patients with Disorder of Consciousness. IEEE Transactions on Affective Computing.
Ianof, J. N., & Anghinah, R. (2017). Traumatic brain injury: An EEG point of view. Dementia & neuropsychologia, 11(1), 3-5.
Ibanez, A., Melloni, M., Huepe, D., Helgiu, E., Rivera-Rei, A., Canales-Johnson, A., ... & Moya, A. (2012). What event-related potentials (ERPs) bring to social neuroscience?. Social neuroscience, 7(6), 632-649.
Liu, Y., Sourina, O., Liew, H. P., Salem, H. S., & Ang, E. (2017). Human factors evaluation in maritime virtual simulators using mobile EEG-based neuroimaging. Transdisciplinary Engineering: A Paradigm Shift, 5, 261-268.
Luck, S. J. (2005). An introduction to the event-related potential technique. MIT Press. Page 304 - Chapter 8.
Malik, A. S., & Amin, H. U. (2017). Designing EEG experiments for studying the brain: Design code and example datasets. Academic Press.
Nandi, A., Xhafa, F., Subirats, L., & Fort, S. (2021). Real-time emotion classification using eeg data stream in e-learning contexts. Sensors, 21(5), 1589.
Nidal, K., & Malik, A. S. (Eds.). (2014). EEG/ERP analysis: methods and applications. Crc Press.
Padfield, N., Zabalza, J., Zhao, H., Masero, V., & Ren, J. (2019). EEG-based brain-computer interfaces using motor-imagery: Techniques and challenges. Sensors, 19(6), 1423.
Price, J., & Budzynski, T. (2009). Anxiety, EEG patterns, and neurofeedback. Introduction to quantitative EEG and neurofeedback: Advanced theory and applications, 453-470.
Ramirez, R., & Vamvakousis, Z. (2012, December). Detecting emotion from EEG signals using the emotive epoc device. In International Conference on Brain Informatics (pp. 175-184). Springer, Berlin, Heidelberg.
Schneider, D., Zickerick, B., Thönes, S., & Wascher, E. (2020). Encoding, storage, and response preparation—Distinct EEG correlates of stimulus and action representations in working memory. Psychophysiology, 57(6), e13577.
Siuly, S., Li, Y., & Zhang, Y. (2016). EEG signal analysis and classification. IEEE Trans Neural Syst Rehabilit Eng, 11, 141-144.
Song, Z., Liu, C., Shi, R., Zhang, M., Wang, H., & Mei, Y. (2020). Neural activities during the evaluation of luxury goods-to-service brand extension: An event-related potentials (ERPs) study. Journal of Neuroscience, Psychology, and Economics, 13(3), 127.
Szurhaj, W., Lamblin, M. D., Kaminska, A., & Sediri, H. (2015). EEG guidelines in the diagnosis of brain death. Neurophysiologie Clinique/Clinical Neurophysiology, 45(1), 97-104.
Ünal, Ö., Özcan, Ö., Öner, Ö., Akcakin, M., Aysev, A., & Deda, G. (2009). EEG and MRI findings and their relation with intellectual disability in pervasive developmental disorders. World Journal of Pediatrics, 5(3), 196-200.
Yadava, M., Kumar, P., Saini, R., Roy, P. P., & Dogra, D. P. (2017). Analysis of EEG signals and its application to neuromarketing. Multimedia Tools and Applications, 76(18), 19087-19111.