Machine learning-based analysis of operator pupillary response to assess cognitive workload in clinical ultrasound imaging.

Journal: Computers in biology and medicine
Published Date: Jun 20, 2021

Abstract

INTRODUCTION: Pupillometry, the measurement of eye pupil diameter, is a well-established and objective modality correlated with cognitive workload. In this paper, we analyse the pupillary response of ultrasound imaging operators to assess their cognitive workload, captured while they undertake routine fetal ultrasound examinations. Our experiments and analysis are performed on real-world datasets obtained using remote eye-tracking under natural clinical environmental conditions.

Authors

  • Harshita Sharma
    Institute of Biomedical Engineering, University of Oxford, Oxford, UK.
  • Lior Drukker
    Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Aris T Papageorghiou
    Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, OX3 9DU, UK.
  • J Alison Noble
    Institute of Biomedical Engineering (IBME), University of Oxford, Oxford, England, UK.

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