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首页> 美国卫生研究院文献>International Journal of Telemedicine and Applications >Effect of Wireless Channels on Detection and Classification of Asthma Attacks in Wireless Remote Health Monitoring Systems
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Effect of Wireless Channels on Detection and Classification of Asthma Attacks in Wireless Remote Health Monitoring Systems

机译：无线通道对无线远程健康监控系统中哮喘发作检测和分类的影响

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摘要

This paper aims to study the performance of support vector machine (SVM) classification in detecting asthma attacks in a wireless remote monitoring scenario. The effect of wireless channels on decision making of the SVM classifier is studied in order to determine the channel conditions under which transmission is not recommended from a clinical point of view. The simulation results show that the performance of the SVM classification algorithm in detecting asthma attacks is highly influenced by the mobility of the user where Doppler effects are manifested. The results also show that SVM classifiers outperform other methods used for classification of cough signals such as the hidden markov model (HMM) based classifier specially when wireless channel impairments are considered.
机译：本文旨在研究支持向量机（SVM）分类在无线远程监控场景中检测哮喘发作的性能。研究无线信道对SVM分类器决策的影响，以便从临床角度确定不建议传输的信道条件。仿真结果表明，SVM分类算法在检测哮喘发作中的性能受到用户移动性的显着影响，其中多普勒效应已得到体现。结果还表明，SVM分类器优于其他用于咳嗽信号分类的方法（例如基于隐马尔可夫模型（HMM）的分类器），特别是在考虑了无线信道损害的情况下。

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