Autoregressive model order property for sleep EEG.
- Author:
Tao WANG
1
;
Guohui WANG
;
Huanqing FENG
Author Information
1. Institute of Biomedical Engineering, University of Science & Technology of China, Hefei 230026, China.
- Publication Type:Journal Article
- MeSH:
Delta Rhythm;
Electroencephalography;
Humans;
Models, Neurological;
Regression Analysis;
Signal Processing, Computer-Assisted;
Sleep Stages;
physiology
- From:
Journal of Biomedical Engineering
2004;21(3):394-396
- CountryChina
- Language:Chinese
-
Abstract:
Traditional sleep scoring system describes the sleep EEG characterized by features in time domain as well as frequency domain. Power Spectral Density (PSD) is one of the well-used methods to observe the occurrence of specified rhythms. However, the parameter model based PSD estimation is used with the assumption that the model order is determined as low as possible through prior knowledge. This paper briefs the development of Autoregressive Model Order (ARMO) criterion, and provides the distribution of ARMOs for specified sleep EEG, which shows that ARMOs concentrate on several well separated regions that are indicative of the microstructure and transition states. This study suggests the promising perspective of ARMO as a special EEG feature for weighing complexity, randomness and rhythm components.
