(Best Paper Award) Enhancing Nursing Care Records with A Spoken Dialogue System based on Smartphones

Reviewed, Featured
Tittaya Mairittha, Nattaya Mairittha, Sozo Inoue,
The 40th Joint Conference on Asia-Pacific Association of Medical Informatics (APAMI)
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8 pages
Background and Objective: This study describes the integration of a spoken dialogue system and
nursing records on an Android smartphone application intending to help nurses reduce documentation
time and improve the overall experience of a healthcare setting. The application also incorporates with
collecting personal sensor data and activity labels for activity recognition.
Methods: We developed a joint model based on a bidirectional long-short term memory and conditional random fields (Bi-LSTM-CRF) to identify user intention and extract record details from user
utterances. Then, we transformed unstructured data into record inputs on the smartphone application.
Results: The joint model achieved the highest F1-score at 96.79%. Moreover, we conducted an experiment to demonstrate the proposed model’s capability and feasibility in recording in realistic settings.
Our preliminary evaluation results indicate that when using the dialogue-based, we could increase the
percentage of documentation speed to 58.13% compared to the traditional keyboard-based.
Conclusions: Based on our findings, we highlight critical and promising future research directions
regarding the design of the efficient spoken dialogue system and nursing records.

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