IoT in Radiology: Using Raspberry Pi to Automatically Log Telephone Calls in the Reading Room

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Abstract

The work environment for medical imaging such as distractions, ergonomics, distance, temperature, humidity, and lighting conditions generates a paucity of data and is difficult to analyze. The emergence of Internet of Things (IoT) with decreasing cost of single-board computers like Raspberry Pi makes creating customized hardware to collect data from the clinical environment within the reach of a clinical imaging informaticist. This article will walk the reader through a series of basic project using a variety sensors and devices in conjunction with a Pi to gather data, culminating in a complex example designed to automatically detect and log telephone calls.

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The online version of this article (10.1007/s10278-018-0081-z) contains supplementary material, which is available to authorized users.

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Do telephone call interruptions have an impact on radiology resident diagnostic accuracy?

Brad Balint, Scott D Steenburg, Hongbu Lin … (2014)

The purpose of this study was to measure the effect of distractions, in the form of telephone call interruptions, on radiology resident diagnostic accuracy.

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Author and article information

Contributors

Po-Hao Chen:

ORCID: http://orcid.org/0000-0001-7698-5289

po-hao.chen@uphs.upenn.edu

Journal

Journal ID (nlm-ta): J Digit Imaging

Journal ID (iso-abbrev): J Digit Imaging

Title: Journal of Digital Imaging

Publisher: Springer International Publishing (Cham )

ISSN (Print): 0897-1889

ISSN (Electronic): 1618-727X

Publication date (Electronic): 3 May 2018

Publication date PMC-release: 3 May 2018

Publication date (Print): June 2018

Volume: 31

Issue: 3

Pages: 371-378

Affiliations

[1 ]ISNI 0000 0004 1936 8972, GRID grid.25879.31, Department of Radiology, Perelman School of Medicine, , University of Pennsylvania, ; 3400 Spruce Street, Philadelphia, PA 19104 USA

[2 ]ISNI 0000 0004 0435 0884, GRID grid.411115.1, Musculoskeletal Imaging, Department of Radiology, , Hospital of the University of Pennsylvania, ; 3737 Market Street, Mailbox #4, Philadelphia, PA 19104 USA

[3 ]ISNI 0000000122986657, GRID grid.34477.33, Department of Radiology, , University of Washington, ; 1959 NE Pacific St, Box 357115, Seattle, WA 98195 USA

Author information

Po-Hao Chen http://orcid.org/0000-0001-7698-5289

Article

Publisher ID: 81

DOI: 10.1007/s10278-018-0081-z

PMC ID: 5959834

PubMed ID: 29725966

SO-VID: 3afed9eb-63ca-4f88-bf2e-7aadafc01e4e

License:

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.