A pilot study to detect human circadian rhythms using a novel thoracic temperature sensor
Abstract
Perturbations 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.