Particle filter-based parameter estimation in a model of the human circadian rhythm

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Abstract

Recent insights into the effects of light on human health call for a more human-centric approach in automatic lighting control systems. We contribute to the provisioning of lighting settings tailored to the needs of individuals by addressing the challenge of predicting the response of an individual’s circadian rhythm to light exposure. Existing models of the human circadian rhythm are not tailored to individual physiological characteristics such as intrinsic circadian period, light sensitivity and age. We propose to improve model accuracy by using Bayesian statistical inference to estimate the values of model parameters that reflect these physiological characteristics. We illustrate our generic method by applying to a combination of two popular models of the circadian rhythm. By processing individual light exposure- and actigraphy data recoded during a field trial with 20 human subjects with a Particle Filter, we estimate each subject’s intrinsic circadian period. When correlating these to the subjects’ Munich Chronotype Questionnaire Midsleep on Free Days time, a significant relationship was found: r > 0.6 and p < 0.01. This shows the proposed method has good potential for improving model accuracy.
Original languageEnglish
Title of host publicationProceedings of the 2018 Symposium on Information Theory and Signal Processing in the Benelux
EditorsLuuk Spreeuwers, Jasper Goseling
Place of PublicationEnschede
PublisherTwente University
Pages35-45
Number of pages11
ISBN (Electronic)978-90-365-4570-9
Publication statusPublished - May 2018
Event2018 Symposium on Information Theory and Signal Processing in the Benelux (SITB 2018) - University of Twente, Enschede, Netherlands
Duration: 31 May 20181 Jun 2018
https://www.utwente.nl/en/eemcs/sitb2018/

Conference

Conference2018 Symposium on Information Theory and Signal Processing in the Benelux (SITB 2018)
Abbreviated titleSITB 2018
Country/TerritoryNetherlands
CityEnschede
Period31/05/181/06/18
Internet address

Keywords

  • circadian rhythm
  • parameter estimation
  • particle filters (PF)
  • light

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