Preprint Article Version 1 This version not peer reviewed

Thermal Signature Based Sleep Analysis Sensor

Version 1 : Received: 26 April 2017 / Approved: 26 April 2017 / Online: 26 April 2017 (12:27:38 CEST)

A peer-reviewed article of this Preprint also exists.

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

Journal reference: Informatics 2017, 4, 37
DOI: 10.3390/informatics4040037

Abstract

This paper address the development of a new technic 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-minutes each. Each of these cycles is composed of a succession of several stages of sleep, more or less deep. The analysis of sleep is usually done using a 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). The recording is done 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 30-second 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 "agitated 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.

Subject Areas

thermopile sensor; actimetry; thermal camera, data classification; tele-medicine; polysomnography;

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