Development of an automatic sleep-wake staging method for rats

Ting Ying Wei, Chung Ping Young

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The study proposed an automated sleep-wake scoring system by using the features of electroencephalogram (EEG) and electromyogram (EMG). The method of normalization has been used to reduce the difference of features between the subjects. The proposed system would automatically discriminate the sleep-wake states into both three-state (waking, NREM and REM) and five-state (waking, NREM stage 1, NREM stage 2, transition sleep, and REM). The automated scoring results were compared with the manual scoring results that scored by the experts. The results of global agreement between the automated scoring and experts consensus in three-state scoring are 92.5% (κ=0.88) and 95.3% (κ=0.91) in five-state scoring. The results indicated that the performance of the automated sleep-wake staging system has highly reliability and accuracy.

Original languageEnglish
Title of host publication2016 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467391726
DOIs
Publication statusPublished - 2016 Aug 4
Event11th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016 - Benevento, Italy
Duration: 2016 May 152016 May 18

Publication series

Name2016 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016 - Proceedings

Other

Other11th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2016
CountryItaly
CityBenevento
Period16-05-1516-05-18

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Instrumentation

Fingerprint Dive into the research topics of 'Development of an automatic sleep-wake staging method for rats'. Together they form a unique fingerprint.

Cite this