生物医学工程学杂志

生物医学工程学杂志

生物阻抗身份识别研究

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本研究旨在根据生物电阻抗理论和模式识别算法, 对不同的人进行生物电阻抗的测量并进行身份识别。本文利用AD5933芯片设计阻抗采集电路来采集不同人手掌处的生物电阻抗, 获得1~100 kHz频率激励下的阻抗谱信息, 计算阻抗曲线的分段频率值作为特征参数。为了提高识别率和防止过度拟合, 将被测人员分成训练集和测试集, 设计了一个3层的向后传播(BP)神经网络模型, 对样本进行训练和预测。研究结果表明, BP神经网络对测试样本能进行有效识别, 训练集的准确率达到97.62%, 验证集的准确率达到88.79%, 测试集的准确率达到86.34%, 综合的识别准确率为94.22%。该网络可以很好地识别出已存在于训练网络中的人和不属于训练网络的陌生人, 验证了基于生物电阻抗的模式识别方法对身份进行辨识的可行性与可靠性, 为身份识别提供了一个简单有效的补充性技术。

Based on bioelectrical impedance theory and pattern recognition algorithm, we in this study measured varieties of people's bioelectrical impedance in hands and identified different people according to their bioelectrical impedance. We designed a bioelectrical impedance collection circuit with AD5933 chip to measure the impedance in different people's hands, and we obtained the bioelectrical impedance spectrum for each person under 1-100 kHz electrical stimulation. We calculated the segmentation slopes of bioelectrical impedance spectrum, and took the slopes as characteristic parameters. In order to promote the recognition rate and prevent the overfitting of the model, we divided the people into the training set and the test set, and designed a 3 layer back propagation neural network model to train and test the samples. The results showed that back propagation neural network model could identify the test set effectively. The recognition rate of the training sets was as high as 97.62%, recognition rate of validation sets was 88.79%, recognition rate of test sets was 86.34%, and the synthetical recognition rate was 94.22%. It gives a clue that the network can perfectly recognize people in the training network as well as strangers that comes from the outside of the tests. Our work can verify the feasibility and reliability of using bioelectrical impedance and pattern recognition algorithm for identification, and can provide a simple and supplementary way to identify people.

关键词: 模式识别; 身份识别; 生物电阻抗; 向后传播神经网络

Key words: pattern recognition; identification; bioelectrical impedance; back propagation neural network

引用本文: 何想, 覃元元, 苏明亮, 江宇宁, 王新安. 生物阻抗身份识别研究. 生物医学工程学杂志, 2016, 33(4): 609-615. doi: 10.7507/1001-5515.20160102 复制

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