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Related Experiment Videos

Acceptance of a speech interface for biomedical data collection

M A Grasso1, D Ebert, T Finin

  • 1Segue Biomedical Computing, Laurel, Maryland, USA. grasso@cs.umbc.edu

Proceedings : a Conference of the American Medical Informatics Association. AMIA Fall Symposium
|January 1, 1997
PubMed
Summary

A multimodal speech interface improved data entry speed and accuracy in medical informatics. Perceptual structure enhanced this speech interface for collecting histopathology data, boosting user acceptance.

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Area of Science:

  • Medical Informatics
  • Human-Computer Interaction
  • Speech Technology

Background:

  • Data entry is a significant bottleneck in medical informatics applications.
  • Speech interfaces offer a potential solution to improve data collection efficiency.
  • Histopathology data collection requires accurate and rapid input.

Purpose of the Study:

  • To evaluate the impact of perceptual structure on a multimodal speech interface for histopathology data collection.
  • To assess the influence of interface design on user performance (speed and accuracy).
  • To identify factors affecting user acceptance of novel speech-based data entry systems.

Main Methods:

  • An experimental study was conducted to compare interface designs.
  • A multimodal interface combining speech recognition and direct manipulation was developed.

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  • The study measured data entry speed and accuracy using the developed interface.

    • Main Results:

    • The perceptually structured multimodal interface significantly increased data entry speed.
    • Accuracy in collecting histopathology data was also enhanced by the structured interface.
    • User acceptance was positively influenced by the improved performance metrics.

    Conclusions:

    • Perceptually structured multimodal speech interfaces can effectively address data entry bottlenecks in medical informatics.
    • Optimizing interface design through perceptual structuring leads to better user performance and acceptance.
    • This approach shows promise for improving clinical data collection workflows.