Literature DB >> 17194621

Impact of noise and other factors on speech recognition in anaesthesia.

Alexandre Alapetite1.   

Abstract

INTRODUCTION: Speech recognition is currently being deployed in medical and anaesthesia applications. This article is part of a project to investigate and further develop a prototype of a speech-input interface in Danish for an electronic anaesthesia patient record, to be used in real time during operations.
OBJECTIVE: The aim of the experiment is to evaluate the relative impact of several factors affecting speech recognition when used in operating rooms, such as the type or loudness of background noises, type of microphone, type of recognition mode (free speech versus command mode), and type of training.
METHODS: Eight volunteers read aloud a total of about 3600 typical short anaesthesia comments to be transcribed by a continuous speech recognition system. Background noises were collected in an operating room and reproduced. A regression analysis and descriptive statistics were done to evaluate the relative effect of various factors.
RESULTS: Some factors have a major impact, such as the words to be recognised, the type of recognition and participants. The type of microphone is especially significant when combined with the type of noise. While loud noises in the operating room can have a predominant effect, recognition rates for common noises (e.g. ventilation, alarms) are only slightly below rates obtained in a quiet environment. Finally, a redundant architecture succeeds in improving the reliability of the recognitions.
CONCLUSION: This study removes some uncertainties regarding the feasibility of introducing speech recognition for anaesthesia records during operations, and provides an overview of the interaction of several parameters that are traditionally studied separately.

Entities:  

Mesh:

Year:  2006        PMID: 17194621     DOI: 10.1016/j.ijmedinf.2006.11.007

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  4 in total

1.  Using a depth-sensing infrared camera system to access and manipulate medical imaging from within the sterile operating field.

Authors:  Matt Strickland; Jamie Tremaine; Greg Brigley; Calvin Law
Journal:  Can J Surg       Date:  2013-06       Impact factor: 2.089

2.  A usability framework for speech recognition technologies in clinical handover: a pre-implementation study.

Authors:  Linda Dawson; Maree Johnson; Hanna Suominen; Jim Basilakis; Paula Sanchez; Dominique Estival; Barbara Kelly; Leif Hanlen
Journal:  J Med Syst       Date:  2014-05-15       Impact factor: 4.460

3.  Capturing patient information at nursing shift changes: methodological evaluation of speech recognition and information extraction.

Authors:  Hanna Suominen; Maree Johnson; Liyuan Zhou; Paula Sanchez; Raul Sirel; Jim Basilakis; Leif Hanlen; Dominique Estival; Linda Dawson; Barbara Kelly
Journal:  J Am Med Inform Assoc       Date:  2014-10-21       Impact factor: 4.497

Review 4.  A systematic review of speech recognition technology in health care.

Authors:  Maree Johnson; Samuel Lapkin; Vanessa Long; Paula Sanchez; Hanna Suominen; Jim Basilakis; Linda Dawson
Journal:  BMC Med Inform Decis Mak       Date:  2014-10-28       Impact factor: 2.796

  4 in total

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