No abstract

ECG signal, a kind of internal characteristics of the human body, which reflects the electrical activity of the heart, has multiple excellent features such as difficult to duplicate, hard to forge, unique, stable and so on. In this paper, the identification of ECG signal is studied based on the theory of wavelet transform. First of all, we introduce the present situation of biometric identification, and then carry out a detailed deduction of wavelet transform to be used and finally simulate the test in MATLAB. The analysis of experimental results shows that the accuracy of identification is high and satisfactory and it is feasible and practical.

No abstract

ECG, a kind of identity information in human identification, can be easily affected by detector's movement and the change of mood. Traditional ECG feature extraction methods require a lot of calculation which increases the computation time in the process of identification. In this paper, we mainly discuss how to seize the main, easy to extract and stable ECG feature, to complete the identification successfully and quickly. And we propose a method of feature extraction that as for intervals, we only choose QRS interval which always maintain the same. Experiments show that the identification speed has been improved when the accuracy of recognition has been little affected.