Feature Extraction Using MS Kinect and Data Fusion in Analysis of Sleep Disorders

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00179906%3A_____%2F15%3A10315849" target="_blank" >RIV/00179906:_____/15:10315849 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/15:00239838 RIV/00216208:11150/15:10315849 RIV/60461373:22340/15:43899502

Výsledek na webu

<a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7347069&isnumber=7347057" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7347069&isnumber=7347057</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IWCIM.2015.7347069" target="_blank" >10.1109/IWCIM.2015.7347069</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Feature Extraction Using MS Kinect and Data Fusion in Analysis of Sleep Disorders

Popis výsledku v původním jazyce

Non-contact methods for the tracking of breathing have found noticeable interest in research in recent years motivated by the obtrusiveness of the traditional approach to sleep disordered breathing diagnosis. The low-priced Kinect device released by Microsoft has emerged as a possible alternative hardware in the field of subject's monitoring aimed at sleep disorders analysis. In this paper we present a method for the reconstruction of the patient's breathing during sleep using the depth maps acquired by Kinect. Preliminary operations of resampling and denoising were performed on the images. A reconstruction of the breathing is then obtained by means of image processing and filtering operations; it is synchronized with the corresponding polysomnographic record, features are extracted from both signals and compared. The strong likeness in the mean of the features extracted from the two records (with mean error of 0.87% in frequency and 9.17% in regularity) supports the view that enhancements of this technique may represent a valid alternative to the present approach to sleep monitoring

Název v anglickém jazyce

Feature Extraction Using MS Kinect and Data Fusion in Analysis of Sleep Disorders

Popis výsledku anglicky

Non-contact methods for the tracking of breathing have found noticeable interest in research in recent years motivated by the obtrusiveness of the traditional approach to sleep disordered breathing diagnosis. The low-priced Kinect device released by Microsoft has emerged as a possible alternative hardware in the field of subject's monitoring aimed at sleep disorders analysis. In this paper we present a method for the reconstruction of the patient's breathing during sleep using the depth maps acquired by Kinect. Preliminary operations of resampling and denoising were performed on the images. A reconstruction of the breathing is then obtained by means of image processing and filtering operations; it is synchronized with the corresponding polysomnographic record, features are extracted from both signals and compared. The strong likeness in the mean of the features extracted from the two records (with mean error of 0.87% in frequency and 9.17% in regularity) supports the view that enhancements of this technique may represent a valid alternative to the present approach to sleep monitoring

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

2015 International workshop on computational intelligence for multimedia understanding (IWCIM)

ISBN

978-1-4673-8457-5

ISSN

—

e-ISSN

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Počet stran výsledku

5

Strana od-do

1-5

Název nakladatele

IEEE

Místo vydání

—

Místo konání akce

Praha

Datum konání akce

29. 10. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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