Sleep Detection using a Depth Camera
In: Lecture Notes in Computer Science, ICCSA 2014, Part I (June 2014), LNCS 8579(824-835)
Abstract
The work at hand presents a method to assess the quality of human sleep within a non-laboratory environment. The monitoring of patients is performed with a Kinect device, thus making the method non-invasive independent of immediate physical contact to subjects. The results of a study carried out as proof of concept are discussed and compared with the polysomnography-based gold standard of sleep analysis.
Keywords: polysomnography, self-monitoring, sleep
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Bibtex
@ARTICLE{krueger2014b,
author = {Kr{\"u}ger, Bj{\"o}rn and V{\"o}gele, Anna and Herwartz, Lukas and Terkatz, Thomas and Weber, Andreas and
Garcia, Carmen and Fietze, Ingo and Penzel, Thomas},
pages = {824--835},
title = {Sleep Detection using a Depth Camera},
journal = {Lecture Notes in Computer Science, ICCSA 2014, Part I},
booktitle = {International Conference on Computational Science and Its Applications (ICCSA) [accepted for
publication]},
volume = {LNCS 8579},
year = {2014},
month = jun,
location = {Minho, Guimaraes, Portugal},
keywords = {polysomnography, self-monitoring, sleep},
abstract = {The work at hand presents a method to assess the quality of human sleep within a non-laboratory
environment. The monitoring of patients is performed with a Kinect device, thus making the method
non-invasive independent of immediate physical contact to subjects. The results of a study carried
out as proof of concept are discussed and compared with the polysomnography-based gold standard of
sleep analysis.}
}