Zheng Minghong, Wu Yi, Weng Changqing
Fuzhou University of International Studies and Trade, Changle District, Fuzhou, Fujian Province, China.
China Academy of Art, LiangzhuSubdistrict, Yuhang District, Hangzhou, Zhejiang Province, China.
Sci Rep. 2025 May 8;15(1):15997. doi: 10.1038/s41598-025-99637-x.
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.
作为一种终身退行性神经疾病，对阿尔茨海默病（AD）患者进行持续的视觉健康监测在医学和设计领域日益受到重视。与此同时，基于物联网（IoT）构建的无线体域网（WBAN）技术已通过卷积神经算法广泛应用于被动式人体健康监测。然而，与传统的主动健康监测相比，WBAN收集的多模态数据及其可视化和分析是否能让AD患者在自身健康方面更加积极主动，并增强利益相关者对AD患者的护理，目前尚不清楚。因此，本研究旨在阐明这一问题，并进行了为期12个月的对照试验。16名AD患者与我们合作，被分为传统体检可视化组和WBAN监测可视化组。在WBAN监测可视化组中，我们创新了一种名为AD-Cloud的数字套件，它由一个具有星型拓扑结构的灵活可穿戴数据收集和传输设备、一个具有高运算能力的用于远程数据可视化的渐进式卷积神经框架以及一个交互式移动应用程序组成。值得强调的是，我们为AD患者创新了行为、生理和心理方面的可视化分析和呈现方法以及WBAN技术和渐进区域增强网络（PRENet）。最后结果表明，在健康监测可视化领域，基于WBAN技术的创新监测可视化设备对AD患者比传统常规医学检查更具积极意义。此外，结果表明，个性化的可解释和可识别的健康数据能让AD患者减轻对自身健康的焦虑，调整身体不佳状况，并增加社交兴趣。最终，通过不断丰富AD患者的电子病例，AD患者未来将能够基于数字生态系统快速获得有效的健康支持。
