A sleep monitoring system based on audio, video and depth information for detecting sleep events

Lyn Chao Ling Chen, Kuan-Wen Chen, Yi Ping Hung

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

The purpose of this study is to develop a non-invasive sleep monitoring system to distinguish sleep disturbances based on multiple sensors. Unlike clinical sleep monitoring which records biological information such as EEG, EOG, and EMG, in this study, we aim to identify occurrences of events from a sleep environment. A device with an infrared depth sensor, a RGB camera, and a four-microphone array is used to detect three types of events: motion events, lighting events, and sound events. Given streams of depth signals and color images, we build two background models to detect movements and lighting effects, and audio signals are scored simultaneously. Moreover, we classify events by an epoch approach algorithm and provide a graphical sleep diagram for browsing corresponding video clips. Experimental results in sleep condition show the efficiency and reliability of our system, and it is convenient and cost-effective to be used in home context.

Original languageEnglish
Article number6890292
JournalProceedings - IEEE International Conference on Multimedia and Expo
Volume2014-September
Issue numberSeptmber
DOIs
StatePublished - 3 Sep 2014
Event2014 IEEE International Conference on Multimedia and Expo, ICME 2014 - Chengdu, China
Duration: 14 Jul 201418 Jul 2014

Keywords

  • Event Detection
  • Image Sequence Analysis
  • Non-invasive Sleep Monitoring

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