A real-time camera-based adaptive breathing monitoring system

Yu Ching Lee, Abdan Syakura, Muhammad Adil Khalil, Ching Ho Wu, Yi Fang Ding, Ching Wei Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Breathing is one of the vital signs used to assess the physical health of a subject. Non-contact-based measurements of both breathing rate and changes in breathing rate help monitor health condition of subjects more flexibly. In this paper, we present an improved real-time camera-based adaptive breathing monitoring system, which includes real time (1) adaptive breathing motion detection, (2) adaptive region of interest detection to eliminate environmental noise, (3) breathing and body movement classification, (4) respiration rate estimation, (5) monitor change in respiration rate to examine overall health of an individual, and (6) online adaptation to lighting. The proposed system does not pose any positional and postural constraint. For evaluation, 30 videos of 15 animals are tested with drugs to simulate various medical conditions and breathing patterns, and the results from the proposed system are compared with the outputs of an existing FDA-approved invasive medical system for patient monitoring. The results show that the proposed method performs significantly correlated RR results to the reference medical device with the correlation coefficient equal to 0.92 and p-value less than 0.001, and more importantly the proposed video-based method is demonstrated to produce alarms 10 to 20 s earlier than the benchmark medical device. [Figure not available: see fulltext.]

Original languageEnglish
Pages (from-to)1285-1298
Number of pages14
JournalMedical and Biological Engineering and Computing
Volume59
Issue number6
DOIs
Publication statusPublished - Jun 2021

Keywords

  • Non-contact-based breathing monitoring
  • Respiration rate measurement
  • Vision-based respiratory rate

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications

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