ArticleScientific reports2025
A digital intelligence visualization health monitoring device for Alzheimer's disease patients based on WBAN technology.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Stage-Wise IoT Solutions for Alzheimer's Disease: A Systematic Review of Detection, Monitoring, and Assistive Technologies.Sensors (Basel, Switzerland) · 2025Pooled it
- AI-enabled digital phenotyping for Alzheimer's disease: a review of multimodal sensor integration and symptom trajectories.Alzheimer's research & therapy · 2026Review
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3 authors.
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Abstract
Continuous visual health monitoring for Alzheimer's disease (AD) patients, as a lifelong degenerative neurological disorder, is increasingly emphasized in medicine and design. Meanwhile, wireless body area network (WBAN) technology, built on the Internet of Things (IoT), has been widely used in passive human health monitoring through convolutional neural algorithms. However, it is unclear whether the multimodal data collected by WBAN and its visualization and analysis allow AD patients to be more active in their own health and enhance stakeholders' care for AD patients compared to traditional active health monitoring. Therefore, this study aimed to demonstrate this question and a 12-month controlled trial was conducted.16 AD patients collaborated with us and were divided into a traditional physical examination visualization group and a WBAN monitoring visualization group. In the WBAN monitoring visualization group, we innovated a digital kit called AD-Cloud, which consists of a flexible wearable data collection and transmission device with a star topology, a progressive convolutional neural framework for remote data visualization with high arithmetic power, and an interactive mobile application. It is worth emphasizing that we have innovated visualization analysis and presentation methods for behavioral, physiological and psychological as well as WBAN techniques and Progressive Region Enhancement Network (PRENet) for AD patients. Finally, it is shown that in the field of health monitoring visualization, innovative monitoring visualization devices based on WBAN technology are more positive for AD patients than traditional routine medical examinations. Also, the results show that personalized interpretable and recognizable health data allow AD patients to reduce anxiety about their health and adjust their poor physical condition and increase their interest in socializing. Ultimately, by continuously enriching the e-cases of AD patients, AD patients will be able to quickly access effective health support based on the digital ecosystem in the future.
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