Artificial neural networks based sleep motion recognition using night vision cameras

Chung Hsien Kuo, Fang Chung Yang, Ming Yuan Tsai, Ming Yih Lee*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

13 Scopus citations


The body movement is one of the most important factors to evaluate the sleep quality. In general, the sleep motion is hardly investigated, and it must take a long time to observe the motion of the patient in terms of a pre-recoded video storage media with high speed playing. This paper proposes an image-based solution to recognize the sleep motions. We use the contact free and IR-based night vision camera to capture the video frames during the sleep of the patient. The video frames are used to recognize the body positions and the body directions such as the "body up", "body down", "body right", and "body left". In addition to the image processing, the proposed artificial neural network (ANN) sleep motion recognition solution is composed of two neural networks. These two neural networks are organized as in a cascade configuration. The first ANN model is used to identify the body position features from the images; and the follower ANN model is constructed based on the features that are identified by the first ANN model to recognize the body direction. Finally, the implementations and the practical results of this work are all illustrated in this paper.

Original languageEnglish
Pages (from-to)79-86
Number of pages8
JournalBiomedical Engineering - Applications, Basis and Communications
Issue number2
StatePublished - 25 04 2004


  • Artificial neural network
  • Machine vision
  • Sleep motion recognition
  • Sleep quality evaluation


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