Beta Wave of Sleep Electroencephalogram Analysis Based on Multiscale Sign Series Entropy
Authors
J.H. Jiang, S.T. Wang, F.Z. Hou, J. Wang, J. Li
Corresponding Author
J.H. Jiang
Available Online July 2015.
- DOI
- 10.2991/aiie-15.2015.108How to use a DOI?
- Keywords
- sleep electroencephalogram; multiscale sign series entropy; clinical diagnosis
- Abstract
Sleep Electroencephalogram (Sleep EEG) detection and treatment can provide the basis for clinical diagnosis and treatment. According to the non-stationary random character of EEG itself, the paper proposed multiscale sign series entropy (MSSE) method and applied it to the state of sleep EEG analysis. Numerical results showed that, MSSE method can effectively differentiate awake period wave and sleep stage wave even if under the influence of the noise. The results show that the algorithm can aid in clinical diagnosis of sleep EEG.
- Copyright
- © 2015, 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 - J.H. Jiang AU - S.T. Wang AU - F.Z. Hou AU - J. Wang AU - J. Li PY - 2015/07 DA - 2015/07 TI - Beta Wave of Sleep Electroencephalogram Analysis Based on Multiscale Sign Series Entropy BT - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering PB - Atlantis Press SP - 395 EP - 398 SN - 1951-6851 UR - https://doi.org/10.2991/aiie-15.2015.108 DO - 10.2991/aiie-15.2015.108 ID - Jiang2015/07 ER -