Evaluating the use of ECG signal in low frequencies as a biometry
作者：
Highlights：
• The viability of identification based on ECG signal sampled in low frequencies.
• Evaluating the use of four feature representations for person identification.
• Majority voting scheme of classified samples provides high accuracy.
• Evaluating the impact of the number of samples for learning and identification.
• Evaluating the biometry scalability when the number of subjects is increased.
摘要
•The viability of identification based on ECG signal sampled in low frequencies.•Evaluating the use of four feature representations for person identification.•Majority voting scheme of classified samples provides high accuracy.•Evaluating the impact of the number of samples for learning and identification.•Evaluating the biometry scalability when the number of subjects is increased.
论文关键词：Biometrics,ECG,Frequency sampling,Majority voting scheme
论文评审过程：Available online 1 October 2013.
论文官网地址：https://doi.org/10.1016/j.eswa.2013.09.028
