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Thermal-Signature-Based Sleep Analysis Sensor

Sorbonne University, Université de Technologie de Compiègne, CNRS, UMR 7338 Biomechanics and Bioengineering, 60200 Compiègne, France
SYEL Laboratory of LIP6 (UPMC), Paris 75005, France
Author to whom correspondence should be addressed.
Informatics 2017, 4(4), 37;
Received: 24 April 2017 / Revised: 30 July 2017 / Accepted: 18 August 2017 / Published: 28 October 2017
(This article belongs to the Special Issue Ambient Assisted living for Improvement of Health and Quality of Life)
This paper addresses the development of a new technique in the sleep analysis domain. Sleep is defined as a periodic physiological state during which vigilance is suspended and reactivity to external stimulations diminished. We sleep on average between six and nine hours per night and our sleep is composed of four to six cycles of about 90 min each. Each of these cycles is composed of a succession of several stages of sleep that vary in depth. Analysis of sleep is usually done via polysomnography. This examination consists of recording, among other things, electrical cerebral activity by electroencephalography (EEG), ocular movements by electrooculography (EOG), and chin muscle tone by electromyography (EMG). Recordings are made mostly in a hospital, more specifically in a service for monitoring the pathologies related to sleep. The readings are then interpreted manually by an expert to generate a hypnogram, a curve showing the succession of sleep stages during the night in 30s epochs. The proposed method is based on the follow-up of the thermal signature that makes it possible to classify the activity into three classes: “awakening,” “calm sleep,” and “restless sleep”. The contribution of this non-invasive method is part of the screening of sleep disorders, to be validated by a more complete analysis of the sleep. The measure provided by this new system, based on temperature monitoring (patient and ambient), aims to be integrated into the tele-medicine platform developed within the framework of the Smart-EEG project by the SYEL–SYstèmes ELectroniques team. Analysis of the data collected during the first surveys carried out with this method showed a correlation between thermal signature and activity during sleep. The advantage of this method lies in its simplicity and the possibility of carrying out measurements of activity during sleep and without direct contact with the patient at home or hospitals. View Full-Text
Keywords: thermopile sensor; actimetry; thermal camera; data classification; tele-medicine; polysomnography thermopile sensor; actimetry; thermal camera; data classification; tele-medicine; polysomnography
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MDPI and ACS Style

Seba, A.; Istrate, D.; Guettari, T.; Ugon, A.; Pinna, A.; Garda, P. Thermal-Signature-Based Sleep Analysis Sensor. Informatics 2017, 4, 37.

AMA Style

Seba A, Istrate D, Guettari T, Ugon A, Pinna A, Garda P. Thermal-Signature-Based Sleep Analysis Sensor. Informatics. 2017; 4(4):37.

Chicago/Turabian Style

Seba, Ali, Dan Istrate, Toufik Guettari, Adrien Ugon, Andrea Pinna, and Patrick Garda. 2017. "Thermal-Signature-Based Sleep Analysis Sensor" Informatics 4, no. 4: 37.

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