標題: Save Muscle Information-Unfiltered EEG Signal Helps Distinguish Sleep Stages
作者: Liu, Gi-Ren
Lustenberger, Caroline
Lo, Yu-Lun
Liu, Wen-Te
Sheu, Yuan-Chung
Wu, Hau-Tieng
應用數學系
Department of Applied Mathematics
關鍵字: EEG;EMG;sleep stage classification;scattering transform
公開日期: 1-四月-2020
摘要: Based on the well-established biopotential theory, we hypothesize that the high frequency spectral information, like that higher than 100Hz, of the EEG signal recorded in the off-the-shelf EEG sensor contains muscle tone information. We show that an existing automatic sleep stage annotation algorithm can be improved by taking this information into account. This result suggests that if possible, we should sample the EEG signal with a high sampling rate, and preserve as much spectral information as possible.
URI: http://dx.doi.org/10.3390/s20072024
http://hdl.handle.net/11536/154615
DOI: 10.3390/s20072024
期刊: SENSORS
Volume: 20
Issue: 7
起始頁: 0
結束頁: 0
顯示於類別:期刊論文