传感器融合的多生命体征系统

IF 1.3 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

IET Networks Pub Date : 2022-10-14 DOI:10.1109/IET-ICETA56553.2022.9971588

Chun-Liang Yang, Yi-Chen Lin, Ming-Che Chiang

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引用次数: 0

摘要

本文提出了一种传感器融合方案，通过预测用户的生理状态来提高传统多生命体征系统的性能。检测用户呼吸产生的二氧化碳、温度和湿度，可以有效地估计用户在进行测量之前是否有足够的休息状态时间。此外，当用户不使用该系统时，它可以监测环境参数，如二氧化碳、温度和湿度。更重要的是，它可以收集用户的生理状态，实现智能多生命体征系统的更高性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multi-Vital Signs System with Sensor Fusion

This paper proposes a scheme with sensor fusion that enhances a traditional multi-vital signs system’s performance by predicting the user’s physiological state. Detecting the user’s carbon dioxide, temperature, and humidity produced by breathing can effectively estimate whether the user has enough resting-state time before conducting measurements. Additionally, when users are not using the system, it can monitor ambient parameters, such as carbon dioxide, temperature, and humidity. More importantly, it can collect the user’s physiological state to achieve the higher performance of an intelligent multi-vital signs system.

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来源期刊

IET Networks COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

5.00

自引率

0.00%

发文量

审稿时长

33 weeks

期刊介绍： IET Networks covers the fundamental developments and advancing methodologies to achieve higher performance, optimized and dependable future networks. IET Networks is particularly interested in new ideas and superior solutions to the known and arising technological development bottlenecks at all levels of networking such as topologies, protocols, routing, relaying and resource-allocation for more efficient and more reliable provision of network services. Topics include, but are not limited to: Network Architecture, Design and Planning, Network Protocol, Software, Analysis, Simulation and Experiment, Network Technologies, Applications and Services, Network Security, Operation and Management.