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dc.contributor.authorChkeir, Alyen
dc.contributor.authorMourad-Chehade, Farahen
dc.contributor.authorHewson, Daviden
dc.contributor.authorDuchêne, Jacquesen
dc.contributor.authorLevi, Francisen
dc.contributor.authorBeau, Jacquesen
dc.contributor.authorMaurice, Moniqueen
dc.contributor.authorKomarzynski, Sandraen
dc.date.accessioned2019-09-19T11:45:32Z
dc.date.available2019-09-19T11:45:32Z
dc.date.issued2016-12-31
dc.identifier.citationChkeir A, Mourad-Chehade F, Hewson DJ, Duchene J, Levi F, Beau J, Maurice M, Komarzynski S (2016) 'A pilot study to detect human circadian rhythms using a novel thoracic temperature sensor', 2016 International Conference on Bio-engineering for Smart Technologies (BioSMART) - Dubai, IEEE.en
dc.identifier.doi10.1109/BIOSMART.2016.7835464
dc.identifier.urihttp://hdl.handle.net/10547/623485
dc.description.abstractPerturbations of circadian rhythms have been related to cancer progression and worsening of metabolic diseases. This paper aims at optimizing the analytical methods suited for the detection of such perturbations using skin temperature signals as a circadian biomarker. Five control subjects were evaluated in this pilot study. Skin temperature was recorded every five minutes for four days. Using a novel thoracic infrared sensor. Four different interpolation methods were compared in order to replace missing values and help subsequently prolong sensor battery life. A Cosinor model was used to characterize circadian rhythms, and compute relevant parameters, with their confidence limits. A divergence study is then proposed to detect changes in these parameters. The results support the enlargement of the sample size and warrant further assessment in cancer patients.
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttps://ieeexplore.ieee.org/abstract/document/7835464en
dc.subjectcircadian rhythmen
dc.subjectinterpolationen
dc.subjectcosinoren
dc.subjectdivergenceen
dc.subjecttemperatureen
dc.titleA pilot study to detect human circadian rhythms using a novel thoracic temperature sensoren
dc.typeConference papers, meetings and proceedingsen
dc.contributor.departmentUniversity of Technology of Troyesen
dc.contributor.departmentUniversity of Bedfordshireen
dc.contributor.departmentWarwick Universityen
dc.contributor.departmentUniversity of Parisen
dc.date.updated2019-09-19T11:43:11Z
html.description.abstractPerturbations of circadian rhythms have been related to cancer progression and worsening of metabolic diseases. This paper aims at optimizing the analytical methods suited for the detection of such perturbations using skin temperature signals as a circadian biomarker. Five control subjects were evaluated in this pilot study. Skin temperature was recorded every five minutes for four days. Using a novel thoracic infrared sensor. Four different interpolation methods were compared in order to replace missing values and help subsequently prolong sensor battery life. A Cosinor model was used to characterize circadian rhythms, and compute relevant parameters, with their confidence limits. A divergence study is then proposed to detect changes in these parameters. The results support the enlargement of the sample size and warrant further assessment in cancer patients.


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