Recent advances in smart wearable sensors for continuous human health monitoring

可穿戴计算机 计算机科学 软件可移植性 可穿戴技术 持续监测 观点 嵌入式系统 数据科学 系统工程 人机交互 工程类 运营管理 程序设计语言 艺术 视觉艺术
作者
Madhusudan B. Kulkarni,R. Sivakumar,Beatriz Prieto‐Simón,Brian W. Pogue
出处
期刊:Talanta [Elsevier BV]
卷期号:272: 125817-125817 被引量:47
标识
DOI:10.1016/j.talanta.2024.125817
摘要

In recent years, the biochemical and biological research areas have shown great interest in a smart wearable sensor because of its increasing prevalence and high potential to monitor human health in a non-invasive manner by continuous screening of biomarkers dispersed throughout the biological analytes, as well as real-time diagnostic tools and time-sensitive information compared to conventional hospital-centered system. These smart wearable sensors offer an innovative option for evaluating and investigating human health by incorporating a portion of recent advances in technology and engineering that can enhance real-time point-of-care-testing capabilities. Smart wearable sensors have emerged progressively with a mixture of multiplexed biosensing, microfluidic sampling, and data acquisition systems incorporated with flexible substrate and bodily attachments for enhanced wearability, portability, and reliability. There is a good chance that smart wearable sensors will be relevant to the early detection and diagnosis of disease management and control. Therefore, pioneering smart wearable sensors into reality seems extremely promising despite possible challenges in this cutting-edge technology for a better future in the healthcare domain. This review presents critical viewpoints on recent developments in wearable sensors in the upcoming smart digital health monitoring in real-time scenarios. In addition, there have been proactive discussions in recent years on materials selection, design optimization, efficient fabrication tools, and data processing units, as well as their continuous monitoring and tracking strategy with system-level integration such as internet-of-things, cyber-physical systems, and machine learning algorithms.
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