Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Developing a wireless speech- and touch-based intelligent comprehensive triage support system.

Polun Chang1, Yu-Hsiang Sheng, Yiing-Yiing Sang

  • 1Institute of Health Informatics and Decision Making, National Yang-Ming University, Taipei, Taiwan, Republic of China. polun@ym.edu.tw

Computers, Informatics, Nursing : CIN
|December 20, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Single-shot wide-field biochemical imaging at 1 kHz frame rate.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Predictive Value of the Lowest Serum Albumin Level During Hospitalization in Patients With Intracerebral Hemorrhage.

Neurology research international·2026
Same author

Interphasial Catalytic Anion Reduction for Stable Anode-Free Sodium-Metal Batteries.

Journal of the American Chemical Society·2026
Same author

Glutathione-responsive molecularly imprinted polymer-based precision delivery system for the synergistic treatment of anti-metabolism and chemodynamic therapy in tumor.

Journal of colloid and interface science·2026
Same author

An informatics competency model for undergraduate nursing students: A quasi-experimental study.

Nurse education today·2026
Same author

Design, Implementation, and Preliminary Evaluation of an Undergraduate Nursing Informatics Literacy Course Based on the ADDIE Model: A Single-Arm Mixed-Methods Study.

Nursing reports (Pavia, Italy)·2026
Same journal

Development and Implementation of the Health Informatics Competency Assessment (HICA): A Pilot Study.

Computers, informatics, nursing : CIN·2026
Same journal

Enhancing Patient Safety: Introducing Barcode Medication Administration (BCMA) Technology at a Cancer Center in Jordan.

Computers, informatics, nursing : CIN·2026
Same journal

Nursing Students' Knowledge, Management Skills, and Recognition of Acute Stroke Symptoms: Comparison of Virtual Patient Simulation and Case-Based Learning.

Computers, informatics, nursing : CIN·2026
Same journal

Internet-delivered Psychological Interventions for Patients with Postpartum Depression: A Scoping Review.

Computers, informatics, nursing : CIN·2026
Same journal

Supporting Literature Reviews: A Comparison Between Human and Generative Artificial Intelligence Screening for a Scoping Review.

Computers, informatics, nursing : CIN·2026
Same journal

Surveying Artificial Intelligence (AI) Attitudes, Use, and Competencies Among Nursing Faculty.

Computers, informatics, nursing : CIN·2026
See all related articles

Voice recognition technology shows significant value in mobile nursing. This study found high accuracy and user willingness, suggesting its potential for improving nursing workflows.

Area of Science:

  • Nursing Informatics
  • Human-Computer Interaction
  • Speech Technology

Background:

  • Voice recognition technology (VRT) is underutilized in mobile nursing despite its potential.
  • Limited research exists on VRT's application and effectiveness in nursing settings.
  • Mobile healthcare demands efficient and intuitive technological solutions.

Purpose of the Study:

  • To evaluate the value and performance of VRT in mobile nursing.
  • To assess nurses' accuracy, efficiency, and willingness to use VRT.
  • To explore VRT's utility in an emergency department triage setting.

Main Methods:

  • Developed a VRT system using VB6.0, Microsoft Speech SDK 5.1, and Simplified Chinese.
  • Implemented the system on touchscreen PCs with wireless headsets in an ED triage station.

Related Experiment Videos

  • Enrolled 30 nurses and measured accuracy rate, operation time, and willingness to use (1-10 scale).

    • Main Results:

    • Achieved an average accuracy rate of 99% for voice recognition.
    • Recorded an average operation time of 108 seconds per task.
    • Nurses reported a mean willingness to use score of 8.2 out of 10.

    Conclusions:

    • Multimodal voice recognition techniques offer significant value to mobile nursing.
    • High accuracy and positive user acceptance indicate VRT's potential to enhance nursing practice.
    • VRT can be a valuable tool for improving efficiency and user experience in mobile healthcare.