An embedded system for on field testing of human identification using ECG biometric

P. Zicari, A. Amira, Georg Fischer, J. Mclaughlin
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引用次数: 4

Abstract

In this paper a complete system for on field testing of the human identification using Electrocardiograms (ECG) biometric is proposed. The enrollment and test procedures are realized in software, while the recognition is implemented in real time on an embedded platform. It uses the wearable Vitalsens wireless sensor with ECG electrodes placed on the chest of the person to be identified, the ECG sensors communicate via Bluetooth with the LM058 Bluetooth adapter connected to the RS232 interface of the RC10 Field Programmable Gate Array (FPGA) prototyping board. A new human identification method based on the fiducial independent feature extraction from ECG signals is implemented on the low power Spartan 3L FPGA chip available on the board. The Principal Component Analysis (PCA) is exploited to select the main significant features. The projected ECG signals on the principal components are then compared by using the Euclidian distance metric. By occupying just the 45% of logic resources and 75% of the BRAM blocks, the embedded system reaches an identification accuracy of 90%.
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一种用于心电生物识别人体身份的嵌入式现场测试系统
本文提出了一套完整的基于心电图生物特征的人体识别现场测试系统。注册和测试过程在软件上实现,识别在嵌入式平台上实时实现。它使用可穿戴式Vitalsens无线传感器,将ECG电极放置在待识别人的胸部,ECG传感器通过蓝牙与连接到RC10现场可编程门阵列(FPGA)原型板的RS232接口的LM058蓝牙适配器进行通信。在板上可用的低功耗Spartan 3L FPGA芯片上实现了一种基于心电信号的基准独立特征提取的人体识别新方法。利用主成分分析(PCA)来选择主要的显著特征。然后利用欧几里得距离度量对主分量上的心电信号进行比较。通过只占用45%的逻辑资源和75%的BRAM块,嵌入式系统的识别准确率达到90%。
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