Voice-based control system for smart hospital wards: a pilot study of patient acceptance

Jian, Wen-Shan; Wang, Ju-Yu; Rahmanti, Annisa Ristya; Chien, Shuo-Chen; Hsu, Chun-Kung; Chien, Chia‐Hui; Li, Yu-Chuan; Chen, Chunyou; Chin, Yen-Po; Huang, Chen-Ling

doi:10.1186/s12913-022-07668-1

Cited by 13 publications

(6 citation statements)

References 26 publications

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“…While other studies have used voice-based approaches in other health settings 12,13 , to our knowledge, this is the first study to assess collecting self-reported epidemiology data with a voice-based system (a previous grant that sought to create a voice-based interface did not to our knowledge achieve this objective 14 ). Many more studies are needed to understand the strengths and limitations of different approaches to collect epidemiology data using voice, for example, with different voice-based systems (e.g.…”

Section: Discussionmentioning

confidence: 99%

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"Alexa, I just ate a donut": A pilot study collecting food and drink intake data with voice input

Millard

Johnson

Neaves

et al. 2022

Preprint

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Background Voice-based systems such as Amazon Alexa may be useful to collect self-reported information in real-time from participants of epidemiology studies, using verbal input. We demonstrate the technical feasibility of using Alexa, investigate participant acceptability, and provide an initial evaluation of the validity of the collected data. We use food and drink information as an exemplar. Methods We recruited 45 staff and students at the University of Bristol (UK). Participants were asked to tell Alexa what they ate or drank for 7 days, and also to submit this information using a web form. Questionnaires asked for basic demographic information and about their experience during the study and acceptability of using Alexa. Results Of the 37 participants with valid data, most were 20-39 years old (N=30; 81%) and 23 (62%) were female. Across 29 participants with Alexa and web entries corresponding to the same intake event, 357 Alexa entries (61%) contained the same food/drink information as the corresponding web entry. Participants often reported that Alexa interjected, and this was worse when entering the food and drink information compared with the event date and time. The majority said they would be happy to use a voice-controlled system for future research. Conclusions While usability of our skill was poor, largely due to the conversational nature and because Alexa interjected if there was a pause in speech, participants were mostly open to participating in future research studies using Alexa. Many more studies are needed, in particular, to trial less conversational interfaces.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

"Alexa, I just ate a donut": A pilot study collecting food and drink intake data with voice input

Millard

Johnson

Neaves

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Although other studies have used voice-based approaches in other health settings [ 16 - 19 ], to the best of our knowledge, this is the first study to assess collecting self-reported epidemiology data with a voice-based system (to the best of our knowledge, a previous grant that sought to create a voice-based interface did not achieve this objective [ 20 ]). Furthermore, although our focus was on using this technology for collecting epidemiological data, the results of our study are likely to be useful more broadly, for example, to inform the development of technologies for personalized health care or commercial systems (collecting self-reported data to track behavior).…”

Section: Discussionmentioning

confidence: 99%

Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study

Millard¹,

Johnson²,

Neaves³

et al. 2023

JMIR Mhealth Uhealth

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Background Voice-based systems such as Amazon Alexa may be useful for collecting self-reported information in real time from participants of epidemiology studies using verbal input. In epidemiological research studies, self-reported data tend to be collected using short, infrequent questionnaires, in which the items require participants to select from predefined options, which may lead to errors in the information collected and lack of coverage. Voice-based systems give the potential to collect self-reported information “continuously” over several days or weeks. At present, to the best of our knowledge, voice-based systems have not been used or evaluated for collecting epidemiological data. Objective We aimed to demonstrate the technical feasibility of using Alexa to collect information from participants, investigate participant acceptability, and provide an initial evaluation of the validity of the collected data. We used food and drink information as an exemplar. Methods We recruited 45 staff members and students at the University of Bristol (United Kingdom). Participants were asked to tell Alexa what they ate or drank for 7 days and to also submit this information using a web-based form. Questionnaires asked for basic demographic information, about their experience during the study, and the acceptability of using Alexa. Results Of the 37 participants with valid data, most (n=30, 81%) were aged 20 to 39 years and 23 (62%) were female. Across 29 participants with Alexa and web entries corresponding to the same intake event, 60.1% (357/588) of Alexa entries contained the same food and drink information as the corresponding web entry. Most participants reported that Alexa interjected, and this was worse when entering the food and drink information (17/35, 49% of participants said this happened often; 1/35, 3% said this happened always) than when entering the event date and time (6/35, 17% of participants said this happened often; 1/35, 3% said this happened always). Most (28/35, 80%) said they would be happy to use a voice-controlled system for future research. Conclusions Although there were some issues interacting with the Alexa skill, largely because of its conversational nature and because Alexa interjected if there was a pause in speech, participants were mostly willing to participate in future research studies using Alexa. More studies are needed, especially to trial less conversational interfaces.

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“…Smart hospitals are the main body of intelligent medical care, which can integrate various software and hardware to improve the efficiency of hospital services and management [ 3 ]. On this basis, the smart ward integrates the above technologies in the ward to achieve the purpose of intelligent management of patients, equipment, and ward software and hardware [ 4 ]. Smart ward is the core and focus of smart healthcare.…”

Section: Intelligent Intensive Care Unitmentioning

confidence: 99%

Intelligent Intensive Care Unit: Current and Future Trends

Mao,

Liu,

et al. 2023

Intensive Care Res

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There is a growing demand for intensive care units, but there is a relative shortage of medical staff. Intensive care work is heavy and stressful. Optimizing the working conditions and processes of the intensive care unit is of great significance for improving the work efficiency and the level of diagnosis and treatment in the intensive care unit. The intelligent intensive care unit is a new ward management model gradually developed on the basis of modern science and technology such as communication technology, internet of things, artificial intelligence, robots, and big data. Under this model, the potential risks caused by human factors are greatly reduced, and the monitoring and treatment of patients has been significantly improved. This paper reviews the progress in related fields.

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Voice-based control system for smart hospital wards: a pilot study of patient acceptance

Cited by 13 publications

References 26 publications

"Alexa, I just ate a donut": A pilot study collecting food and drink intake data with voice input

"Alexa, I just ate a donut": A pilot study collecting food and drink intake data with voice input

Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study

Intelligent Intensive Care Unit: Current and Future Trends

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