Usability Engineering for Medical Devices using Artificial Intelligence and Machine Learning Technology

This paper explores how to apply the established IEC 62366-1 usability engineering process for safe and effective use of Artificial Intelligence (AI) and machine learning in medical devices. We identify unique factors specific to AI technology that can impact safe use and integrate these considerations into a comprehensive analysis of IEC 62366-1. This analysis results in a step-by-step guide with practical recommendations for identifying, evaluating, and mitigating use-related risks specific to AI devices.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-22
DOI
https://doi.org/10.5281/zenodo.14203189
Primary Topic
Healthcare Technology and Patient Monitoring
Type
article
Field-Weighted Citation Impact
0.00
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article

Usability Engineering for Medical Devices using Artificial Intelligence and Machine Learning Technology

Zenodo (CERN European Organization for Nuclear Research)
Healthcare Technology and Patient Monitoring
article

Usability Engineering for Medical Devices using Artificial Intelligence and Machine Learning Technology

article en

Abstract

This paper explores how to apply the established IEC 62366-1 usability engineering process for safe and effective use of Artificial Intelligence (AI) and machine learning in medical devices. We identify unique factors specific to AI technology that can impact safe use and integrate these considerations into a comprehensive analysis of IEC 62366-1. This analysis results in a step-by-step guide with practical recommendations for identifying, evaluating, and mitigating use-related risks specific to AI devices.

Zenodo (CERN European Organization for Nuclear Research)
Philips (Finland) (FI), Johner Institut (Germany) (DE), User Interface Design (Germany) (DE), Siemens Healthineers (Germany) (DE), Stryker (Germany) (DE)
Openalex Percentile: Top 42%
Healthcare Technology and Patient Monitoring
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