School of Engineering, The University of Edinburgh, Edinburgh EH9 3FF, UK.
Sensors (Basel). 2022 Nov 5;22(21):8519. doi: 10.3390/s22218519.
The prevalence of chronic diseases and the rapid rise in the aging population are some of the major challenges in our society. The utilization of the latest and unique technologies to provide fast, accurate, and economical ways to collect and process data is inevitable. Industry 4.0 (I4.0) is a trend toward automation and data exchange. The utilization of the same concept of I4.0 in healthcare is termed Healthcare 4.0 (H4.0). Digital Twin (DT) technology is an exciting and open research field in healthcare. DT can provide better healthcare in terms of improved patient monitoring, better disease diagnosis, the detection of falls in stroke patients, and the analysis of abnormalities in breathing patterns, and it is suitable for pre- and post-surgery routines to reduce surgery complications and improve recovery. Accurate data collection is not only important in medical diagnoses and procedures but also in the creation of healthcare DT models. Health-related data acquisition by unobtrusive microwave sensing is considered a cornerstone of health informatics. This paper presents the 3D modeling and analysis of unobtrusive microwave sensors in a digital care-home model. The sensor is studied for its performance and data-collection capability with regards to patients in care-home environments.
慢性病的普遍存在和人口老龄化的迅速增长是我们社会面临的一些主要挑战。利用最新的独特技术,提供快速、准确和经济的数据收集和处理方法是不可避免的。工业 4.0(I4.0)是自动化和数据交换的趋势。在医疗保健中利用相同的 I4.0 概念称为医疗保健 4.0(H4.0)。数字孪生(DT)技术是医疗保健领域令人兴奋和开放的研究领域。DT 可以通过改善患者监测、更好的疾病诊断、中风患者跌倒的检测以及呼吸模式异常的分析来提供更好的医疗保健,并且适用于手术前后的常规操作,以减少手术并发症并促进康复。准确的数据收集不仅在医疗诊断和程序中很重要,而且在医疗保健 DT 模型的创建中也很重要。通过非干扰微波感应进行健康相关数据采集被认为是健康信息学的基石。本文提出了数字养老院模型中非干扰微波传感器的 3D 建模和分析。研究了传感器在养老院环境中对患者的性能和数据收集能力。