Integrating a spoken dialogue system, nursing records, and activity data collection based on smartphones. (October 2021)

• Record Type: Journal Article
• Authors: Mairittha, Tittaya; Mairittha, Nattaya; Inoue, Sozo
• Is Part Of: Computer methods and programs in biomedicine. Volume 210(2021)
• Publication Date: 2021-10
• Subjects: Electronic health record -- Nursing record -- Dialogue system -- Intent classification -- Entity extraction -- Activity recognition; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2021.106364
• Languages: English
• ISSNs: 0169-2607

Abstract

Abstract: 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.