Anomaly detection for sleep EEG signal with Mahalanobis-Taguchi-Gram-Schmidt method
- 10.2991/iceesd-18.2018.118How to use a DOI?
- Anomaly detection, Electroencephalogram(EEG) signal,Mahalanobis-Taguchi-Gram-Schmidt, sleep stages, Signal to Noise ratio
Considering the tedious steps, the poor accuracy and over-subjectivity of human sleep quality judgment artificially, this paper presents an automatic detection algorithm of sleep quality based on Mahalanobis-Taguchi system method. Based on the modeling and analysis of the human brain dual channel EEG signals, the normalized vector of each channel is obtained under different sleep stages. At the same time, the linear independent vector group is subjected to Gram-Schmidt orthogonalization, and the mean value of the signal-to-noise ratio of each sleep stage is calculated by using the Mahalanobis-Taguchi-Gram-Schmidt method. Through analyzing the waveform of the mean signal-to-noise ratio on different sleep stages, the normal and the abnormal sleep quality can be identified.
- © 2018, 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 - Xiaohong Peng AU - Rui Zheng AU - Jiufu Liu AU - Xiaobin Ding PY - 2018/05 DA - 2018/05 TI - Anomaly detection for sleep EEG signal with Mahalanobis-Taguchi-Gram-Schmidt method BT - Proceedings of the 2018 7th International Conference on Energy, Environment and Sustainable Development (ICEESD 2018) PB - Atlantis Press SP - 645 EP - 650 SN - 2352-5401 UR - https://doi.org/10.2991/iceesd-18.2018.118 DO - 10.2991/iceesd-18.2018.118 ID - Peng2018/05 ER -