[微波心脏指纹:基于超宽带生物雷达心脏微动探测的新型非接触式人体识别技术]。

Q4 Medicine
Wei Huang, Wei Ren, Kehan Wang, Zhao Li, Jianqi Wang, Guohua Lu, Fugui Qi
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引用次数: 0

摘要

现有的一次性身份验证技术无法在整个人机交互过程中持续保证用户身份的合法性,往往需要用户的主动配合,这严重限制了其可用性。本研究提出了一种基于超宽带(UWB)生物雷达心脏微动检测的新型非接触式身份识别技术。超宽带生物雷达连续检测到人体心脏表面区域范围维度的多点微动回波后,利用二维主成分分析(2D-PCA)提取每个精确分割的心跳周期中二维图像矩阵的压缩特征,即距离信道-心跳采样点(DC-HBP)矩阵,用于身份识别。在实际测量实验中,基于所提出的多范围-分层和二维-PCA 特征方案以及两种传统的参考特征方案,选取了三个典型的分类器作为代表,在正常呼吸和屏气两种状态下进行心跳识别。结果表明,本文提出的多范围-bin 和 2D-PCA 特征方案的识别效果最好。与最佳范围分区和整体心跳特征方案相比,我们提出的方案的整体平均识别准确率提高了 6.16%(正常呼吸:6.84%;憋气:5.48%)。与多距离单位和整体心跳特征方案相比,我们提出的方案的总体平均准确率提高了 27.42%(正常呼吸:28.63%;屏气:26.21%)。这项研究有望提供一种不受干扰、全天候、非接触和连续的身份验证新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Microwave Heartprint: A novel non-contact human identification technology based on cardiac micro-motion detection using ultra wideband bio-radar].

The existing one-time identity authentication technology cannot continuously guarantee the legitimacy of user identity during the whole human-computer interaction session, and often requires active cooperation of users, which seriously limits the availability. This study proposes a new non-contact identity recognition technology based on cardiac micro-motion detection using ultra wideband (UWB) bio-radar. After the multi-point micro-motion echoes in the range dimension of the human heart surface area were continuously detected by ultra wideband bio-radar, the two-dimensional principal component analysis (2D-PCA) was exploited to extract the compressed features of the two-dimensional image matrix, namely the distance channel-heart beat sampling point (DC-HBP) matrix, in each accurate segmented heart beat cycle for identity recognition. In the practical measurement experiment, based on the proposed multi-range-bin & 2D-PCA feature scheme along with two conventional reference feature schemes, three typical classifiers were selected as representatives to conduct the heart beat identification under two states of normal breathing and breath holding. The results showed that the multi-range-bin & 2D-PCA feature scheme proposed in this paper showed the best recognition effect. Compared with the optimal range-bin & overall heart beat feature scheme, our proposed scheme held an overall average recognition accuracy of 6.16% higher (normal respiration: 6.84%; breath holding: 5.48%). Compared with the multi-distance unit & whole heart beat feature scheme, the overall average accuracy increase was 27.42% (normal respiration: 28.63%; breath holding: 26.21%) for our proposed scheme. This study is expected to provide a new method of undisturbed, all-weather, non-contact and continuous identification for authentication.

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来源期刊
生物医学工程学杂志
生物医学工程学杂志 Medicine-Medicine (all)
CiteScore
0.80
自引率
0.00%
发文量
4868
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