ArticleJMIR mHealth and uHealth2020
The Ubiquitous Cognitive Assessment Tool for Smartwatches: Design, Implementation, and Evaluation Study.
Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Review
- Wearable devices in neurological disorders: a narrative review of status quo and perspectives.Annals of translational medicine · 2025Review
- Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review.JMIR mHealth and uHealth · 2024Article
- The application of unmanned aerial vehicle oblique photography technology in online tourism design.PloS one · 2023Article
- Wearable Devices for Physical Activity and Healthcare Monitoring in Elderly People: A Critical Review.Geriatrics (Basel, Switzerland) · 2021Review
- The most used questionnaires for evaluating the usability of robots and smart wearables: A scoping review.Digital healthArticle
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2 authors.
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Abstract
backgroundCognitive functioning plays a significant role in individuals' mental health, since fluctuations in memory, attention, and executive functions influence their daily task performance. Existing digital cognitive assessment tools cannot be administered in the wild and their test sets are not brief enough to capture frequent fluctuations throughout the day. The ubiquitous availability of mobile and wearable devices may allow their incorporation into a suitable platform for real-world cognitive assessment.
objectiveThe aims of this study were threefold: (1) to evaluate a smartwatch-based tool for the assessment of cognitive performance, (2) to investigate the usability of this tool, and (3) to understand participants' perceptions regarding the application of a smartwatch in cognitive assessment.
methodsWe built the Ubiquitous Cognitive Assessment Tool (UbiCAT) on a smartwatch-based platform. UbiCAT implements three cognitive tests-an Arrow test, a Letter test, and a Color test-adapted from the two-choice reaction-time, N-back, and Stroop tests, respectively. These tests were designed together with domain experts. We evaluated the UbiCAT test measures against standard computer-based tests with 21 healthy adults by applying statistical analyses significant at the 95% level. Usability testing for each UbiCAT app was performed using the Mobile App Rating Scale (MARS) questionnaire. The NASA-TLX (Task Load Index) questionnaire was used to measure cognitive workload during the N-back test. Participants rated perceived discomfort of wearing a smartwatch during the tests using a 7-point Likert scale. Upon finishing the experiment, an interview was conducted with each participant. The interviews were transcribed and semantic analysis was performed to group the findings.
resultsPearson correlation analysis between the total correct responses obtained from the UbiCAT and the computer-based tests revealed a significant strong correlation (r=.78, P<.001). One-way analysis of variance (ANOVA) showed a significant effect of the N-back difficulty level on the participants' performance measures. The study also demonstrated usability ratings above 4 out of 5 in terms of aesthetics, functionality, and information. Low discomfort (<3 out of 7) was reported by our participants after using the UbiCAT. Seven themes were extracted from the transcripts of the interviews conducted with our participants.
conclusionsUbiCAT is a smartwatch-based tool that assesses three key cognitive domains. Usability ratings showed that participants were engaged with the UbiCAT tests and did not feel any discomfort. The majority of the participants were interested in using the UbiCAT, although some preferred computer-based tests, which might be due to the widespread use of personal computers. The UbiCAT can be administered in the wild with mentally ill patients to assess their attention, working memory, and executive function.
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