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Article

Save Muscle Information–Unfiltered EEG Signal Helps Distinguish Sleep Stages

1
Department of Mathematics, National Chen-Kung University, Tainan 701, Taiwan
2
Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, 8092 Zurich, Switzerland
3
Department of Thoracic Medicine, Healthcare Center, Chang Gung Memorial Hospital, School of Medicine, Chang Gung University, New Taipei 33302, Taiwan
4
Sleep Center, Shuang Ho Hospital, Taipei Medical University, New Taipei City 110, Taiwan
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Department of Applied Mathematics, National Chiao Tung University, Hsinchu 30010, Taiwan
6
Department of Mathematics and Department of Statistical Science, Duke University, 120 Science Dr. Durham, NC 27708, USA
7
Mathematics Division, National Center for Theoretical Sciences, Taipei 106, Taiwan
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(7), 2024; https://doi.org/10.3390/s20072024
Received: 5 February 2020 / Revised: 25 March 2020 / Accepted: 27 March 2020 / Published: 3 April 2020
(This article belongs to the Special Issue Artificial Intelligence in Medical Sensors)
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. View Full-Text
Keywords: EEG; EMG; sleep stage classification; scattering transform EEG; EMG; sleep stage classification; scattering transform
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MDPI and ACS Style

Liu, G.-R.; Lustenberger, C.; Lo, Y.-L.; Liu, W.-T.; Sheu, Y.-C.; Wu, H.-T. Save Muscle Information–Unfiltered EEG Signal Helps Distinguish Sleep Stages. Sensors 2020, 20, 2024. https://doi.org/10.3390/s20072024

AMA Style

Liu G-R, Lustenberger C, Lo Y-L, Liu W-T, Sheu Y-C, Wu H-T. Save Muscle Information–Unfiltered EEG Signal Helps Distinguish Sleep Stages. Sensors. 2020; 20(7):2024. https://doi.org/10.3390/s20072024

Chicago/Turabian Style

Liu, Gi-Ren, Caroline Lustenberger, Yu-Lun Lo, Wen-Te Liu, Yuan-Chung Sheu, and Hau-Tieng Wu. 2020. "Save Muscle Information–Unfiltered EEG Signal Helps Distinguish Sleep Stages" Sensors 20, no. 7: 2024. https://doi.org/10.3390/s20072024

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