Online Machine Learning Audiometry.

Journal: Ear and hearing
Published Date: Jan 1, 2019

Abstract

OBJECTIVES: A confluence of recent developments in cloud computing, real-time web audio and machine learning psychometric function estimation has made wide dissemination of sophisticated turn-key audiometric assessments possible. The authors have combined these capabilities into an online (i.e., web-based) pure-tone audiogram estimator intended to empower researchers and clinicians with advanced hearing tests without the need for custom programming or special hardware. The objective of this study was to assess the accuracy and reliability of this new online machine learning audiogram method relative to a commonly used hearing threshold estimation technique also implemented online for the first time in the same platform.

Authors

  • Dennis L Barbour
  • Rebecca T Howard
    Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, Missouri, USA.
  • Xinyu D Song
    1Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA; 2Program in Audiology and Communication Sciences, Washington University in St. Louis, St. Louis, Missouri, USA; and 3Department of Computer Science & Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.
  • Nikki Metzger
    Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, Missouri, USA.
  • Kiron A Sukesan
    Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, Missouri, USA.
  • James C DiLorenzo
    Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, Missouri, USA.
  • Braham R D Snyder
    Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, Missouri, USA.
  • Jeff Y Chen
    Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, Missouri, USA.
  • Eleanor A Degen
    Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, Missouri, USA.
  • Jenna M Buchbinder
    Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, Missouri, USA.
  • Katherine L Heisey
    Laboratory of Sensory Neuroscience and Neuroengineering, Department of Biomedical Engineering, Washington University in St. Louis, Missouri, USA.

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