Optode design space exploration for clinically-robust non-invasive fetal oximetry

Daniel D. Fong, Vivek J. Srinivasan, Kourosh Vali, Soheil Ghiasi

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Non-invasive transabdominal fetal oximetry (TFO) has the potential to improve delivery outcomes by providing physicians with an objective metric of fetal well-being during labor. Fundamentally, the technology is based on sending light through the maternal abdomen to investigate deep fetal tissue, followed by detection and processing of the light that returns (via scattering) to the outside of the maternal abdomen. The placement of the photodetector in relation to the light source critically impacts TFO system performance, including its operational robustness in the face of fetal depth variation. However, anatomical differences between pregnant women cause the fetal depths to vary drastically, which further complicates the optical probe (optode) design optimization. In this paper, we present a methodology to solve this problem. We frame optode design space exploration as a multi-objective optimization problem, where hardware complexity (cost) and performance across a wider patient population (robustness) form competing objectives. We propose a model-based approach to characterize the Pareto-optimal points in the optode design space, through which a specific design is selected. Experimental evaluation via simulation and in vivo measurement on pregnant sheep support the efficacy of our approach.

Original languageEnglish (US)
Article numbera63
JournalACM Transactions on Embedded Computing Systems
Volume18
Issue number5s
DOIs
StatePublished - Oct 2019

Keywords

  • Design optimization
  • Design space exploration
  • Internet of medical things
  • Medical cyber-physical systems
  • Multi-objective optimization
  • Non-invasive fetal oximetry

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture

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