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Iris: A Low-Cost Telemedicine Robot to Support Healthcare Safety and Equity During a Pandemic

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Pervasive Computing Technologies for Healthcare (PH 2021)

Abstract

The COVID-19 pandemic exacerbated problems of already overwhelmed healthcare ecosystems. The pandemic worsened long-standing health disparities and increased stress and risk of infection for frontline healthcare workers (HCWs). Telemedical robots offer great potential to both improve HCW safety and patient access to high-quality care, however, most of these systems are prohibitively expensive for under-resourced healthcare organizations, and difficult to use. In this paper, we introduce Iris, a low-cost, open hardware/open software telemedical robot platform. We co-designed Iris with front-line HCWs to be usable, accessible, robust, and well-situated within the emergency medicine (EM) ecosystem. We tested Iris with 15 EM physicians, who reported high usability, and provided detailed feedback critical to situating the robot within a range of EM care delivery contexts, including under-resourced ones. Based on these findings, we present a series of concrete design suggestions for those interested in building and deploying similar systems. We hope this will inspire future work both in the current pandemic and beyond.

Work supported by the National Science Foundation under Grant No. IIS-1527759 and the Institute for Engineering and Medicine (IEM).

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Author information

Authors and Affiliations

  1. Computer Science and Engineering, UC San Diego, San Diego, USA

    Sachiko Matsumoto, Sanika Moharana, Nimisha Devanagondi & Laurel D. Riek

  2. Emergency Medicine, UC San Diego, San Diego, USA

    Leslie C. Oyama & Laurel D. Riek

Authors
  1. Sachiko Matsumoto
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  2. Sanika Moharana
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  3. Nimisha Devanagondi
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  4. Leslie C. Oyama
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  5. Laurel D. Riek
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Corresponding author

Correspondence to Sachiko Matsumoto .

Editor information

Editors and Affiliations

  1. Holon Institute of Technology, Holon, Israel

    Hadas Lewy

  2. Holon Institute of Technology, Holon, Israel

    Refael Barkan

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Matsumoto, S., Moharana, S., Devanagondi, N., Oyama, L.C., Riek, L.D. (2022). Iris: A Low-Cost Telemedicine Robot to Support Healthcare Safety and Equity During a Pandemic. In: Lewy, H., Barkan, R. (eds) Pervasive Computing Technologies for Healthcare. PH 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 431. Springer, Cham. https://doi.org/10.1007/978-3-030-99194-4_9

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  • DOI: https://doi.org/10.1007/978-3-030-99194-4_9

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-99194-4

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