Abstract
Neurofeedback is a kind of bio feedback that induces the brain wave pattern or the regional cerebral blood flow (rCBF). For the last thirty years, this technique was clinically applied in order to increase the effect of the psychotherapy. However, most of the studies which were carried out until now were just simple ones that analyze the patterns of the brain waves according to specific stimulations. It seems that the studies related to the environmental factors for the specific time have not been carried out yet. There was a problem caused by the difference according to the surrounding environment when a specific type of stimulation is applied to a specific patient. Such a problem was an obstacle in the clinical utilization of this technique. In order to solve such a problem, this study has analyzed the characteristics of the brain waves along with the changes of the surrounding environment for the time when the stimulation is applied to the patient. Based on the results, the trend for inducing emotional changes in the environmental factors was analyzed. Also, a way to utilize brain waves for stable neurofeedback treatments, and related training techniques and health-care tools, which were not influenced by the environmental changes, was suggested.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hsiu, H., Hsu, W.-C., Hsu, C.L., Huang, S.-M., Hsu, T.-L., Wang, Y.-Y.L.: Spectral analysis on the microcirculatory laser Doppler signal of the acupuncture effect. In: IEEE-EMBS 2008, 30th Annual International Conference of the 2008 Engineering in Medicine and Biology Society, pp. 2916–2919 (August 2008)
Li, N., Wang, J., Deng, B., Dong, F.: An analysis of EEG when acupuncture with Wavelet entropy. In: IEEE-EMBS 2008. 30th Annual International Conference of the 2008 Engineering in Medicine and Biology Society, pp. 1108–1111 (August 2008)
He, W.-X., Yan, X.-G., Chen, X.-P., Liu, H.: Nonlinear Feature Extraction of Sleeping EEG Signals. In: IEEE-EMBS 2005, 27th Annual International Conference of the 2005 Engineering in Medicine and Biology Society, pp. 4614–4617 (September 2005)
Murata, T., Akutagawa, M., Kaji, Y., Shichijou, F.: EEG Analysis Using Moving Average-type Neural Network. In: IEEE-EMBS 2008, 30th Annual International Conference of the 2008 Engineering in Medicine and Biology Society, pp. 169–172 (August 2008)
Kaji, Y., Akutagawa, M., Shichijo, F., Nagashino, H., Kinouchi, Y., Nagahiro, S.: EEG analysis using neural networks to detect change of brain conditions during operations. In: IFMBE Proceedings, pp. 1079–1082 (April 2006)
Sun, Y., Ye, N., Xu, X.: EEG Analysis of Alcoholics and Controls Based on Feature Extraction. In: The 8th International Conference on Signal Processing (2006)
Zhang, S.Z., Kawabata, H., Liu, Z.-Q.: EEG Analysis using Fast Wavelet Transform. In: IEEE International Conference on Systems, Man, and Cybernetics, pp. 2959–2964 (October 2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Shin, JH., Park, DH. (2011). Analysis for Characteristics of Electroencephalogram (EEG) and Influence of Environmental Factors According to Emotional Changes. In: Lee, G., Howard, D., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2011. Communications in Computer and Information Science, vol 206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24106-2_63
Download citation
DOI: https://doi.org/10.1007/978-3-642-24106-2_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24105-5
Online ISBN: 978-3-642-24106-2
eBook Packages: Computer ScienceComputer Science (R0)