Nonlinear smoothing of core body temperature data with random gaps and outliers (DRAGO)

A. Parekh, I. W. Selesnick, A. Baroni, O. M. Bubu, A. W. Varga, D. M. Rapoport, I. Ayappa, E. M. Blessing, R. S. Osorio

Research output: Chapter in Book/Report/Conference proceedingChapter


Core body temperature measurement using an ingestible pill has been proven effective for field-based ambulatory applications. The ingestible pill overcomes many impracticalities related with traditional methods of assessing core body temperature; however, it suffers from two key issues: random gaps due to missing data and outliers due to electromagnetic interference. In this chapter we detail a principled convex optimization-based framework for pre-processing the raw core body temperature signal. The proposed framework assumes that the raw core body temperature signal consists of two components: a smooth low-frequency component and a transient component with sparse outliers. We derive a computationally efficient algorithm using the majorization-minimization procedure and show its performance on simulated data. Finally, we demonstrate utility of the proposed method for estimating the circadian rhythm of core body temperature in cognitively normal elderly.

Original languageEnglish (US)
Title of host publicationBiomedical Signal Processing
Subtitle of host publicationInnovation and Applications
PublisherSpringer International Publishing
Number of pages22
ISBN (Electronic)9783030674946
ISBN (Print)9783030674939
StatePublished - Apr 12 2021


  • Circadian rhythm
  • Convex optimization
  • Core body temperature
  • Lomb-Scargle
  • Sparse regularization

ASJC Scopus subject areas

  • General Engineering
  • General Biochemistry, Genetics and Molecular Biology
  • General Medicine


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