Individual Identification Using ECG SignalsW

• 作者: Alaa Seif Maher Sabbah Mohamad El-Abed Mohamad O. Diab
• 来源期刊: 电脑和通信(英文)
• 学科: 医学
• 关键词: BIOMETRICS ECG Signals Fiducial Features Discrete Wavelet TRANSFORM (DWT) MULTILAYER PERCEPTRON (MLP)
• 年，卷（期）: dnhtxyw_2018,（1）
• 页码范围: 74-80
• 页数: 7页
• 分类号: R73

摘要

The electrocardiogram (ECG) signal used for diagnosis and patient monitoring, has recently emerged as a biometric recognition tool. Indeed, ECG signal changes from one person to another according to health status, heart geometry and anatomy among other factors. This paper forms a comparative study between different identification techniques and their performances. Previous works in this field referred to methodologies implementing either set of fiducial or set non-fiducial features. In this study we show a comparison of the same data using a fiducial feature set and a non-fiducial feature set based on statistical calculation of wavelet coefficient. High identification rates were measured in both cases, non-fiducial using Discrete Meyer (dmey) wavelet outperformed the rest at 98.65.