title: Virtual thermistor.
abstract: The present paper unveils a methodology to recover the breathing signal from the subject's nostrils through thermal imaging. The resulting functionality is equivalent to that of a thermistor, but it is materialized in a contact-free manner. First, the nostril region is segmented and it is tracked over time through coalitional tracking. The mean thermal signal of the nostril region carries the breathing information. This information is extracted through wavelets analysis. The method has been tested on 20 healthy individuals. The frequencies of the breathing signals determined via the imaging computation were compared with those of the corresponding signals acquired with thermistors. The high degree of agreement between the two measurement methods confirms the validity of the proposed approach and opens the way for clinical applications.
authors.affiliation: Computational Physiology Lab, Department of Computer Science, University of Houston, Houston, Texas 77204-3010, USA. jinfei@cs.uh.edu
authors.forename: Jin
authors.initials: J
authors.lastname: Fei
authors.forename: Ioannis
authors.initials: I
authors.lastname: Pavlidis
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009666:Nose / Q000502:physiology*; D012119:Respiration; D013817:Thermography / Q000379:methods*