Fuzzy clustering and bidirectional long short-term memory for sleep stages classification

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

This research uses feature representation with Bidirectional Long Short Term Memory (Bi-LSTM) as a final classifier. Feature learning is performed after feature extraction and aims to get the optimal represented feature. The feature representation mechanism is required as a pre-process for Bi-LSTM because Bi-LSTM is not reliable when directly processing raw data or feature extraction results. The focus of the research is to investigate the influence of cluster number of Fuzzy Clustering on Bi-LSTM performance. Specifically, the study examined the proposed method of sleep stage classification in which the data used were polysomnogram. From the testing result, it's found that increasing the number of clusters tends to increase the performance of sleep stage classification. Experiments using nine groups at the feature representation stage have the highest performance with the value of F-measure of 72.75%.

Original languageEnglish
Title of host publicationProceedings - 2017 International Conference on Soft Computing, Intelligent System and Information Technology
Subtitle of host publicationBuilding Intelligence Through IOT and Big Data, ICSIIT 2017
EditorsHenry Novianus Palit, Leo Willyanto Santoso
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages11-16
Number of pages6
ISBN (Electronic)9781467398992
DOIs
Publication statusPublished - 16 Jan 2018
Event5th International Conference on Soft Computing, Intelligent System and Information Technology, ICSIIT 2017 - Denpasar, Bali, Indonesia
Duration: 26 Sep 201729 Sep 2017

Publication series

NameProceedings - 2017 International Conference on Soft Computing, Intelligent System and Information Technology: Building Intelligence Through IOT and Big Data, ICSIIT 2017
Volume2018-January

Conference

Conference5th International Conference on Soft Computing, Intelligent System and Information Technology, ICSIIT 2017
Country/TerritoryIndonesia
CityDenpasar, Bali
Period26/09/1729/09/17

Keywords

  • Sleep disorder
  • bidirectional long short-term memory
  • classification
  • fuzzy clustering

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