Automatic Classification of Neonatal Sleep-Wake States Based on Facial Video Analysis

Yohei Mukai, Kento Morita, Nobu C. Shirai, Tetsushi Wakabayashi, Harumi Shinkoda, Asami Matsumoto, Yukari Noguchi, Masako Shiramizu

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

Abstract

Premature babies are admitted to the NICU (Neonatal Intensive Care Unit) for several weeks and generally placed under high medical supervision. To provide a better environment to them, some researchers investigate the affection of light and noise in the NICU on the formation of the sleep-wake cycle of the newborn called Circadian rhythm. These researches require the optimal evaluation method of the sleep-wake state. The visual assessment by nurses do not guarantee enough inter-tester reliability, and the measurement puts an additional burden on them. The conventional sleep-wake states discrimination method requires attachment devices on the subject's body. This paper proposes the automatic classification method of the sleep-wake states of neonates by using only facial information. In this research, we extract gradient features and spatio-temporal HOGV features from 3,600 face image frames (1 minute). According to Blazelton's method, this study classifies the sleep-wake states into six classes by using machine learning techniques. Support Vector Machine and Random Forest were used in the experiment. The spatio-temporal HOGV feature is an extension of the HOG feature to the time domain. The experiments using two kinds of feature quantities and classifiers showed that the highest accuracy rate (54.4%) was obtained by the gradient feature and Random Forest. This result suggested the possibility of improving accuracy by combining facial information with body movement and other conventional features.

Original languageEnglish
Title of host publicationProceedings of 4th International Conference on Information Technology Research
Subtitle of host publicationBridging Digital Divide Through Multidisciplinary Research, ICITR 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728161990
DOIs
Publication statusPublished - Dec 10 2019
Event4th International Conference on Information Technology Research, ICITR 2019 - Moratuwa, Sri Lanka
Duration: Dec 10 2019Dec 13 2019

Publication series

NameProceedings of 4th International Conference on Information Technology Research: Bridging Digital Divide Through Multidisciplinary Research, ICITR 2019

Conference

Conference4th International Conference on Information Technology Research, ICITR 2019
Country/TerritorySri Lanka
CityMoratuwa
Period12/10/1912/13/19

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Social Sciences (miscellaneous)

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