SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Hasanain B, Boyd AD, Edworthy J, Bolton ML. Appl. Ergon. 2017; 58: 500-514.

Affiliation

University at Buffalo, State University of New York, Department of Industrial and Systems Engineering, Buffalo, NY, USA. Electronic address: mbolton@buffalo.edu.

Copyright

(Copyright © 2017, Elsevier Publishing)

DOI

10.1016/j.apergo.2016.07.008

PMID

27633247

Abstract

The failure of humans to respond to auditory medical alarms has resulted in numerous patient injuries and deaths and is thus a major safety concern. A relatively understudied source of response failures has to do with simultaneous masking, a condition where concurrent sounds interact in ways that make one or more of them imperceptible due to physical limitations of human perception. This paper presents a method, which builds on a previous implementation, that uses a novel combination of psychophysical modeling and formal verification with model checking to detect masking in a modeled configuration of medical alarms. Specifically, the new method discussed here improves the original method by adding the ability to detect additive masking while concurrently improving method usability and scalability. This paper describes how these additions to our method were realized. It then demonstrates the scalability and detection improvements via three different case studies.

RESULTS and future research are discussed.

Copyright © 2016 Elsevier Ltd. All rights reserved.


Language: en

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print