Developing a Wireless Speech- and Touch-Based Intelligent Comprehensive Triage Support System
Abstract
The implementation of voice recognition technology has been expected to occur in mobile healthcare settings, but it is the least studied solution in nursing. The objective of this study is to examine its value to mobile nursing. The study was done at a triage station in an emergency department. The system was developed using VB6.0, Microsoft Speech SDK 5.1 and the Simplified Chinese Language pack, and was installed on touchscreen PCs with wireless headsets. Thirty nurses were enrolled. Accuracy rate and operation time were used to measure the subjects' performance. A "willingness to use" score on a scale of 1 to 10 was used to measure subjects' preference for the system. The results showed that the average accuracy rate was 99%, the average operation time was 108 seconds, and the mean "willingness to use" rating was 8.2. This study demonstrates the value of multimodal voice recognition techniques to mobile nursing.
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Several studies reported feedback concerned with customization or availability of feature options: 2 studies commented positively, and 3 studies desired more features and more control.
“However, several studies reported feedback concerned with customization or availability of feature options, with 2 studies commenting on it positively (eg, having both voice and touch modes to allow hands-free work and rapid data input on a triage system for nurses) [8,35], and 3 studies desiring more features and more control [33,37,48].”
From The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (2020) · cites this paper as [8]
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The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review
Milne-Ives, M., de Cock, C., Lim, E., Shehadeh, M. H., de Pennington, N., Mole, G., Normando, E., & Meinert, E. (2020) · Journal of Medical Internet Research · doi:10.2196/20346 · Cited by 626 · see citing works
The Use and Promise of Conversational Agents in Digital Health
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Joseph, J., Moore, Z. E. H., Patton, D., O'Connor, T., & Nugent, L. E. (2020) · Journal of Clinical Nursing · doi:10.1111/jocn.15261 · Cited by 49 · see citing works
- Authors
- CHANG, P., SHENG, Y.-H., SANG, Y.-Y., & WANG, D.-W.
- Affiliations
- National Yang Ming University (TW)
- Taipei Veterans General Hospital (TW)
- ORCID
- CHANG, POLUN
- Venue
- CIN: Computers, Informatics, Nursing
- Published
- 2008-01
- Volume
- 26
- Issue
- 1
- Pages
- 31-38
- ISSN
- 1538-2931 (ISSN-L)
- OpenAlex
- W2068433921
- Cited by
- 10
- References
- 13
- Citations by year
- 2026: 1 · 2025: 1 · 2023: 1 · 2021: 1 · 2020: 2 · 2018: 1
- FWCI
- 2.21
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- CIN Computers Informatics Nursing (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Keywords
- voice recognition, speech recognition, mobile nursing, emergency department triage, wireless headset, multimodal recognition, nurse performance, user acceptance, Mandarin Chinese
- MeSH terms
- Medication Errors, Surveys and Questionnaires, Triage, User-Computer Interface
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