基于雷达的呼吸障碍识别的FPGA实现

2019 IEEE MTT-S International Microwave Biomedical Conference (IMBioC) Pub Date : 2019-05-01 DOI:10.1109/IMBIOC.2019.8777851

Chen Feng, Heng Zhao, Qian Liu, Hong Hong, Chen Gu, Xiaohua Zhu

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引用次数: 3

摘要

本文实现了一种紧凑的呼吸障碍识别系统。呼吸障碍的时域波形由数字中频多普勒雷达传感器捕获。然后利用FPGA实现呼吸障碍识别模块，包括特征提取和kNN算法。实验结果表明，分类六种呼吸模式(五种呼吸障碍和正常呼吸)的总体准确率为73%。

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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Implementation of Radar-based Breathing Disorder Recognition Using FPGA

In this paper, a compact breathing disorder recognition system is implemented. The time-domain waveform breathing disorder is captured by the digital-IF Doppler radar sensor. Then the breathing disorder recognition module including the feature extraction and kNN algorithm is achieved using the FPGA. The experimental results show that the overall accuracy for classifying six breathing patterns (five breathing disorders and normal breathing) is 73%.

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来源期刊

2019 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)

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