Breathing Analysis Using Thermal and Depth Imaging Camera Video Records

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63516787" target="_blank" >RIV/70883521:28140/17:63516787 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21730/17:00318549 RIV/00216208:11150/17:10367936 RIV/60461373:22340/17:43903862

Result on the web

<a href="http://www.mdpi.com/1424-8220/17/6/1408/htm" target="_blank" >http://www.mdpi.com/1424-8220/17/6/1408/htm</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s17061408" target="_blank" >10.3390/s17061408</a>

Result language

angličtina

Original language name

Breathing Analysis Using Thermal and Depth Imaging Camera Video Records

Original language description

The paper is devoted to the study of facial region temperature changes using a simple thermal imaging camera and to the comparison of their time evolution with the pectoral area motion recorded by the MS Kinect depth sensor. The goal of this research is to propose the use of video records as alternative diagnostics of breathing disorders allowing their analysis in the home environment as well. The methods proposed include (i) specific image processing algorithms for detecting facial parts with periodic temperature changes; (ii) computational intelligence tools for analysing the associated videosequences; and (iii) digital filters and spectral estimation tools for processing the depth matrices. Machine learning applied to thermal imaging camera calibration allowed the recognition of its digital information with an accuracy close to 100% for the classification of individual temperature values. The proposed detection of breathing features was used for monitoring of physical activities by the home exercise bike. The results include a decrease of breathing temperature and its frequency after a load, with mean values −0.16 °C/min and −0.72 bpm respectively, for the given set of experiments. The proposed methods verify that thermal and depth cameras can be used as additional tools for multimodal detection of breathing patterns.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20601 - Medical engineering

Project

—

Continuities

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sensors

ISSN

1424-8220

e-ISSN

—

Volume of the periodical

17

Issue of the periodical within the volume

6

Country of publishing house

CH - SWITZERLAND

Number of pages

10

Pages from-to

"nestrankovano"

UT code for WoS article

000404553900224

EID of the result in the Scopus database

2-s2.0-85020920353