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Session: Poster session 2 (Odd numbers)
Session starts: Friday 27 January, 10:00
Presentation starts: 10:00

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Nemanja Cabrilo (Eindhoven University of Technology)
Charikleia Papatsimpa (Signify)
Jean-Paul Linnartz (Eindhoven University of Technology)

Abstract:
The central biological clock in the brain has a near-24h rhythmicity that is a main determinant of individuals’ sleep/wake cycles. It also orchestrates the daily rhythms of hormonal secretion and behaviour such as subjective alertness and performance[1]. Having a solution to determine and track the state of an individual’s internal circadian state can allow us to make major steps to optimize human daily rhythms, from the use of light for improving sleep quality to precision medicine, diagnosing neurological disorders and optimizing drug delivery. Some estimates[2] of the circadian state demonstrated that, even if not up to clinical standards, can greatly enhance human-centric lighting to improve wellbeing of, for example, office, industry or warehouse workers. In a quest to investigate the use of wearable sensing for tracking the underlying circadian process, we developed a model that combines a physiology-based model of the human biological clock with non-invasive but possibly in-accurate ambulatory data (in particular actigraphy data) in a statistical framework[3]. Nowadays we are conducting a field study to validate our model in a real-life setting and to test to what extent this leads to meaningful estimates. We compare model-based predictions based on wearable data (CamnTech MotionWatch8) against the “gold standard” circadian state estimation, namely, individual subject’s bathyphase, or timing of the daily Core Body Temperature (CBT) nadir (minimum point) which is a widely accepted circadian phase marker[4]. CBT is continuously being recorded with BodyCAP e-Celsius Performance ingestible e-capsule(s). Beyond, we aim to assess further physiological signals and identify the best possible predictors, with reasonable user comfortability, as non-invasive circadian biomarkers, for instance: Skin temperature (DSL1922L temperature logger), Heart-Rate Variability (Movisense EcgMove4), Electro-Dermal Activity (Empatica E4 wristband). Accurate and unobtrusive estimation of the exact circadian phase can unlock the potential of numerous applications, possibly including personalized Human-Centric Lighting. Our measurement set-up is unique in its versatility of different sensor modalities and allows a cross-benchmarking. As measurements are being collected at the moment of writing this abstract, the conference paper will primarily address design consideration for the tests, discuss variability of measurements and sensor imperfections combined with early experiences and technical findings.