A fuzzy inference system for sleep staging

Sheng Fu Liang, Ying Huang Chen, Chih En Kuo, Jyun Yu Chen, Sheng Che Hsu

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

6 Citations (Scopus)

Abstract

In this paper, a fuzzy inference system for sleep staging was developed. Nine input variables including temporal and spectrum analyses of the EEG, EOG, and EMG signals were extracted and normalization was applied to these variables to reduce the effect of individual variability. A fuzzy inference system contains fourteen fuzzy rules was designed to classify the 30-s sleep epochs as five sleep stages. Finally, a smoothing process was applied to the scoring results for fine-tuning. The average accuracy of the proposed method applied to 16 all-night polysomnography (PSG) recordings compared with the manual scorings can reach 87 %. This method can integrate with various PSG systems for sleep monitoring in clinical or homecare applications.

Original languageEnglish
Title of host publicationFUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings
Pages2104-2107
Number of pages4
DOIs
Publication statusPublished - 2011 Sep 27
Event2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei, Taiwan
Duration: 2011 Jun 272011 Jun 30

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Other

Other2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
CountryTaiwan
CityTaipei
Period11-06-2711-06-30

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All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

Cite this

Liang, S. F., Chen, Y. H., Kuo, C. E., Chen, J. Y., & Hsu, S. C. (2011). A fuzzy inference system for sleep staging. In FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings (pp. 2104-2107). [6007380] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZY.2011.6007380