Circadian rhythm tracking using core body temperature estimates from wearable sensor data

Rerabek, Martin; Schiboni, Giovanni; Durrer, Lukas; Oliveras, Ruben; Eib, Philippe; Rouchat, Fabien; Probst, Anja; Schmidt, Markus; Kryszczuk, Krzysztof

Publication type:	Conference other
Type of review:	Peer review (abstract)
Title:	Circadian rhythm tracking using core body temperature estimates from wearable sensor data
Authors:	Rerabek, Martin Schiboni, Giovanni Durrer, Lukas Oliveras, Ruben Eib, Philippe Rouchat, Fabien Probst, Anja Schmidt, Markus Kryszczuk, Krzysztof
et. al:	No
Conference details:	7th International Conference on Human Interaction and Emerging Technologies (IHIET), Lausanne, Switzerland, 23-25 April 2022
Issue Date:	2022
Language:	English
Subjects:	Circadian rhythm tracking; Core body temperature; Wearable sensor
Subject (DDC):	610: Medicine and health
Abstract:	The circadian rhythm (CR) in a healthy individual is controlled by the suprachiasmatic nuclei. CR controls physiological functions as a response to the natural day-night cycle hence it has a period close to 24 hours. A disruption of the healthy CR is often associated with pathologies on physiological and psychological levels, ranging from mood shifts, sleep disorders, to neurodegenerative diseases and tumorigenesis. This work aims at accurate, non-invasive, continuous tracking of the changes in core body temperature as a prominent manifestation of the CR. To date, the legacy methods of tracking the core body temperature are either inaccurate (such as skin temperature measurements), or excessively invasive for a long-term deployment (such as digestible thermometer pills, or rectal measurements). We use machine learning techniques to estimate the core body temperature from peripheral physiological signals such as skin temperature, heat flux, acceleration, and heart rate. To acquire data necessary for an estimation of the core body temperature under free living conditions, we used a novel, proprietary, wrist-wearable device featuring temperature, heat flux and accelerometer sensors developed at GreenTEG AG, as well off-the-shelf hardware equipped with a PPG sensor for heart rate monitoring. We created a unique database containing continuous 3-day recordings of peripheral physiological signals from 58 subjects. The reference core body temperature data, necessary for development and evaluation of the proposed algorithms, has been recorded using digestible pills for core body temperature measurements. In this poster, we demonstrate accurate core body temperature estimation from peripheral physiological signals with average rms=0.31 degrees Celsius. The accuracy of core body temperature estimation using the proposed method exceeds that of alternative devices reported in literature. We also evaluated the estimated CR trajectory in comparison to reference using correlation coefficient (ρ=0.71) and bias measure (Δ =-0.03). Proposed novel sensing technology enables accurate, non-invasive and continuous core body temperature estimation, which is crucial for tracking and detecting minute changes of the circadian rhythm. It holds a great potential to non-invasively provide relevant information about health conditions in healthy individual and clinical patients.
URI:	https://digitalcollection.zhaw.ch/handle/11475/26865
Fulltext version:	Published version
License (according to publishing contract):	Licence according to publishing contract
Departement:	Life Sciences and Facility Management
Organisational Unit:	Institute of Computational Life Sciences (ICLS)
Published as part of the ZHAW project:	Sensor for a wearable device for early detection of symptoms of possible neurodegenerative diseases
Appears in collections:	Publikationen Life Sciences und Facility Management

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Rerabek, M., Schiboni, G., Durrer, L., Oliveras, R., Eib, P., Rouchat, F., Probst, A., Schmidt, M., & Kryszczuk, K. (2022). Circadian rhythm tracking using core body temperature estimates from wearable sensor data. 7th International Conference on Human Interaction and Emerging Technologies (IHIET), Lausanne, Switzerland, 23-25 April 2022.

Rerabek, M. et al. (2022) ‘Circadian rhythm tracking using core body temperature estimates from wearable sensor data’, in 7th International Conference on Human Interaction and Emerging Technologies (IHIET), Lausanne, Switzerland, 23-25 April 2022.

M. Rerabek et al., “Circadian rhythm tracking using core body temperature estimates from wearable sensor data,” in 7th International Conference on Human Interaction and Emerging Technologies (IHIET), Lausanne, Switzerland, 23-25 April 2022, 2022.

RERABEK, Martin, Giovanni SCHIBONI, Lukas DURRER, Ruben OLIVERAS, Philippe EIB, Fabien ROUCHAT, Anja PROBST, Markus SCHMIDT und Krzysztof KRYSZCZUK, 2022. Circadian rhythm tracking using core body temperature estimates from wearable sensor data. In: 7th International Conference on Human Interaction and Emerging Technologies (IHIET), Lausanne, Switzerland, 23-25 April 2022. Conference presentation. 2022

Rerabek, Martin, Giovanni Schiboni, Lukas Durrer, Ruben Oliveras, Philippe Eib, Fabien Rouchat, Anja Probst, Markus Schmidt, and Krzysztof Kryszczuk. 2022. “Circadian Rhythm Tracking Using Core Body Temperature Estimates from Wearable Sensor Data.” Conference presentation. In 7th International Conference on Human Interaction and Emerging Technologies (IHIET), Lausanne, Switzerland, 23-25 April 2022.

Rerabek, Martin, et al. “Circadian Rhythm Tracking Using Core Body Temperature Estimates from Wearable Sensor Data.” 7th International Conference on Human Interaction and Emerging Technologies (IHIET), Lausanne, Switzerland, 23-25 April 2022, 2022.