Sleep EEG analysis Based on the Multiscale Jenson-Shannon Divergence
- 10.2991/ameii-16.2016.128How to use a DOI?
- multi-scale, JSD, sleep EEG signals
Sleep EEG signals analysis is a hotspot of research recently, this paper, by using nonlinear dynamics theory knowledge, JSD algorithm and multi-scale JSD algorithm is proposed for some individual conscious period and NREM sleep stage I analyzed the research of EEG signals, and the use of SPSS statistical software to verify the veracity and reliability of the experiment, at the same time, with the error bar graph method to analysis the two different states of sleep EEG signals, the results show that both the JSD algorithm and the multi-scale JSD algorithm can effectively distinguish between awake and NREM sleep stage I of EEG signals, these two conditions' EEG signals exist significant differences, The algorithm we proposed can be further used in the study of sleep EEG in installment, which can also provide all kinds of disease diagnosis and treatment of sleep with effective auxiliary function, the research has important practical significance in the future.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhengxia Zhang AU - Jia-Fei Dai AU - Jun Wang AU - Feng-Zhen Hou PY - 2016/04 DA - 2016/04 TI - Sleep EEG analysis Based on the Multiscale Jenson-Shannon Divergence BT - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016) PB - Atlantis Press SP - 643 EP - 648 SN - 2352-5401 UR - https://doi.org/10.2991/ameii-16.2016.128 DO - 10.2991/ameii-16.2016.128 ID - Zhang2016/04 ER -