Correlation analysis between EEG data and facial expressions and sleep behaviors
Aims To date, several methods were presented to assess sleep quality, including subjective and objective methods in the clinic. In the present study, the concept-of-sleep quality assessment method was assessed through EEG data, facial expressions, and sleep behaviours and to explore the correlation...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | Brain-Apparatus Communication |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/27706710.2023.2208167 |
| _version_ | 1797685717167505408 |
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| author | Qiongfang Cao Zhongrui Ma Fangfang Liu Yuhan Wang Xiechuan Weng Fan Xu |
| author_facet | Qiongfang Cao Zhongrui Ma Fangfang Liu Yuhan Wang Xiechuan Weng Fan Xu |
| author_sort | Qiongfang Cao |
| collection | DOAJ |
| description | Aims To date, several methods were presented to assess sleep quality, including subjective and objective methods in the clinic. In the present study, the concept-of-sleep quality assessment method was assessed through EEG data, facial expressions, and sleep behaviours and to explore the correlation between EEG data and facial expressions and sleep behavior. Methods Sleep EEG data was collected by The Philips Alice 6LDE system, facial expressions were collected from top, left and right angles by an infrared camera, and sleep behavior was recorded by a full-view camera. EEG data were analyzed by EEGLAB, Noldus FaceReader software and Observer XT analyzed facial expression and sleep behavior. Results The average power of each band of EEG fluctuated up and down during sleep, the frequency of sleep behaviour was the least in the 3-4 h of sleep, and natural facial expression was the largest in the 3-4 h of sleep. And the correlation analysis results showed that the changes in each band under different channels were correlated with facial expressions (p < 0.05). Conclusion This experiment showed the changes in sleep EEG, sleep behaviors and sleep facial expression during sleep, and found the correlation between sleep EEG data and sleep facial expression. |
| first_indexed | 2024-03-12T00:55:20Z |
| format | Article |
| id | doaj.art-9ab2d26748ae425cb007204abcb07fe3 |
| institution | Directory Open Access Journal |
| issn | 2770-6710 |
| language | English |
| last_indexed | 2024-03-12T00:55:20Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Brain-Apparatus Communication |
| spelling | doaj.art-9ab2d26748ae425cb007204abcb07fe32023-09-14T13:24:41ZengTaylor & Francis GroupBrain-Apparatus Communication2770-67102023-12-012110.1080/27706710.2023.22081672208167Correlation analysis between EEG data and facial expressions and sleep behaviorsQiongfang Cao0Zhongrui Ma1Fangfang Liu2Yuhan Wang3Xiechuan Weng4Fan Xu5Department of Public Health, Chengdu Medical CollegeDepartment of psychosomatic medicine, Chengdu Fifth People’s Hospital/Geriatric Diseases Institute of ChengduArt College, Southwest Minzu UniversityDepartment of Public Health, Chengdu Medical CollegeDepartment of Neuroscience, Beijing Institute of Basic Medical SciencesDepartment of Public Health, Chengdu Medical CollegeAims To date, several methods were presented to assess sleep quality, including subjective and objective methods in the clinic. In the present study, the concept-of-sleep quality assessment method was assessed through EEG data, facial expressions, and sleep behaviours and to explore the correlation between EEG data and facial expressions and sleep behavior. Methods Sleep EEG data was collected by The Philips Alice 6LDE system, facial expressions were collected from top, left and right angles by an infrared camera, and sleep behavior was recorded by a full-view camera. EEG data were analyzed by EEGLAB, Noldus FaceReader software and Observer XT analyzed facial expression and sleep behavior. Results The average power of each band of EEG fluctuated up and down during sleep, the frequency of sleep behaviour was the least in the 3-4 h of sleep, and natural facial expression was the largest in the 3-4 h of sleep. And the correlation analysis results showed that the changes in each band under different channels were correlated with facial expressions (p < 0.05). Conclusion This experiment showed the changes in sleep EEG, sleep behaviors and sleep facial expression during sleep, and found the correlation between sleep EEG data and sleep facial expression.http://dx.doi.org/10.1080/27706710.2023.2208167sleepeegfacial expressionsquality assessment |
| spellingShingle | Qiongfang Cao Zhongrui Ma Fangfang Liu Yuhan Wang Xiechuan Weng Fan Xu Correlation analysis between EEG data and facial expressions and sleep behaviors Brain-Apparatus Communication sleep eeg facial expressions quality assessment |
| title | Correlation analysis between EEG data and facial expressions and sleep behaviors |
| title_full | Correlation analysis between EEG data and facial expressions and sleep behaviors |
| title_fullStr | Correlation analysis between EEG data and facial expressions and sleep behaviors |
| title_full_unstemmed | Correlation analysis between EEG data and facial expressions and sleep behaviors |
| title_short | Correlation analysis between EEG data and facial expressions and sleep behaviors |
| title_sort | correlation analysis between eeg data and facial expressions and sleep behaviors |
| topic | sleep eeg facial expressions quality assessment |
| url | http://dx.doi.org/10.1080/27706710.2023.2208167 |
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