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Applying Augmented Reality to Enable Automated and Low-Cost Data Capture from Medical Devices

Published: 03 June 2016 Publication History

Abstract

As an alternative to building custom electronic devices that connect to mobile phones (via Bluetooth or USB), we present a new approach using Augmented Reality (AR) and machine vision to digitally recognize a biomedical device and capture readings automatically. In the context of developing countries, this approach enables easy integration with low-cost devices, without the need for designing any electronics or obtaining new FDA regulatory approval. As an example, we illustrate the use of AR with a peak flow meter, a device used in the diagnosis and treatment of respiratory disease. In our mobile application, the AR graphic overlay is used to provide feedback to patients and doctors by displaying personalized reference values. Comparing the automated readings from this device to manual readings, our mobile application had a mean error of 5.8 L/min and a correlation of 0.99. A small user study was also conducted in an India field clinic with three health staff (two nurses and a doctor). Following one minute of instruction, the automated readings from the participants had a mean error of 5.5 L/min and a correlation of 0.99 compared to manual readings, with a median task duration of 17.5 seconds. This small case study illustrates how AR can be used to capture medical device data on a mobile phone and help automate the data recording tasks performed by health workers in developing countries. This technology can also be used in developed countries, enabling patients to automatically record readings from similar devices at home using their smart phones.

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Cited By

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  • (2019)Study of Human–Computer Interaction in Augmented RealitySoft Computing for Problem Solving10.1007/978-981-15-0184-5_71(835-846)Online publication date: 28-Nov-2019
  • (2018)Pulmonary Screener: A Mobile Phone Screening Tool for Pulmonary and Respiratory Disease2018 IEEE Global Humanitarian Technology Conference (GHTC)10.1109/GHTC.2018.8601821(1-7)Online publication date: Oct-2018
  • (2018)Ex Vivo BiosignaturesHealth and Wellness Measurement Approaches for Mobile Healthcare10.1007/978-3-030-01557-2_3(51-104)Online publication date: 23-Sep-2018
  • Show More Cited By
  1. Applying Augmented Reality to Enable Automated and Low-Cost Data Capture from Medical Devices

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    Published In

    cover image ACM Other conferences
    ICTD '16: Proceedings of the Eighth International Conference on Information and Communication Technologies and Development
    June 2016
    427 pages
    ISBN:9781450343060
    DOI:10.1145/2909609
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    In-Cooperation

    • Google Inc.
    • Microsoft: Microsoft
    • University of Michigan: University of Michigan

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 03 June 2016

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    Author Tags

    1. Android
    2. Augmented reality
    3. asthma
    4. consumer health
    5. lung health
    6. medical devices
    7. mobile health
    8. peak flow meter

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    Cited By

    View all
    • (2019)Study of Human–Computer Interaction in Augmented RealitySoft Computing for Problem Solving10.1007/978-981-15-0184-5_71(835-846)Online publication date: 28-Nov-2019
    • (2018)Pulmonary Screener: A Mobile Phone Screening Tool for Pulmonary and Respiratory Disease2018 IEEE Global Humanitarian Technology Conference (GHTC)10.1109/GHTC.2018.8601821(1-7)Online publication date: Oct-2018
    • (2018)Ex Vivo BiosignaturesHealth and Wellness Measurement Approaches for Mobile Healthcare10.1007/978-3-030-01557-2_3(51-104)Online publication date: 23-Sep-2018
    • (2016)A mobile platform for automated screening of asthma and chronic obstructive pulmonary disease2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)10.1109/EMBC.2016.7591897(5192-5195)Online publication date: Aug-2016

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