School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen 518055, China.
School of Information Engineering, Jimei University, Xiamen 361021, China.
Sensors (Basel). 2018 Nov 26;18(12):4138. doi: 10.3390/s18124138.
Electrocardiograph (ECG) technology is vital for biometric security, and blood oxygen is essential for human survival. In this study, ECG signals and blood oxygen levels are combined to increase the accuracy and efficiency of human identification and verification. The proposed scheme maps the combined biometric information to a matrix and quantifies it as a sparse matrix for reorganizational purposes. Experimental results confirm a much better identification rate than in other ECG-related identification studies. The literature shows no research in human identification using the quantization sparse matrix method with ECG and blood oxygen data combined. We propose a multi-dimensional approach that can improve the accuracy and reduce the complexity of the recognition algorithm.
心电图（ECG）技术对于生物识别安全至关重要，而血氧对于人类生存则是必不可少的。在这项研究中，我们将心电图信号和血氧水平相结合，以提高人类识别和验证的准确性和效率。该方案将组合生物识别信息映射到矩阵中，并将其量化为稀疏矩阵，以进行重组。实验结果证实，与其他心电图相关的识别研究相比，该方案的识别率有了显著提高。文献中没有研究表明，将心电图和血氧数据相结合，使用量化稀疏矩阵方法进行人类识别。我们提出了一种多维方法，可以提高识别算法的准确性并降低其复杂性。
