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In this paper, a new approach for automatic analysis of single lead ECG for human recognition is proposed and evaluated. Following the pre-processing step, the ECG stream is partitioned into separate windows where each window includes single beat of ECG signal. After successful QRS detection, various temporal, amplitude and AR coefficients are extracted and used as an input to a classifier in order to identify the individuals. In this work, proposed system has been tested using records from three different publicly available ECG databases. Signal pre-processing techniques, applied parameter extraction methods and some intermediate and final classification results are presented in this paper. that PAW yields equivalent performance in terms of accuracy compared to conventional temporal and amplitude feature extraction methods. Even though, PAW is complicated process which needs powerful digital signal processors to overcome the time delay. In this paper, a new approach for automatic analysis of single lead electrocardiogram (ECG) for human recognition and individual identification is proposed. This approach depends on on analytic (Amplitude, Time and Width) and modelling (AR) features extracted from the ECG beat. Obtained results indicate high level of accuracy and shorter processing time needed to identify the individuals. Eighteen analytic and modelling features are extracted to identify individuals and k nearest neighbour (knn) classification algorithm applied in order to classify those features and evaluate the proposed approach. ECG feature selection and extraction using AR modelling has recently been used (9) resulting in accurate classification of various arrhythmia and ventricular arrhythmia conditions. The remainder of this paper is organized as follows. Section II gives a brief description of the techniques used in the pre-processing phase to clean ECG signals of noise and other artefacts. Section III provides a review of QRS detection methods used in this work. Feature selection and extraction methods are discussed in Section IV whilst Section V contains experimental results and discussion of those results. Conclusions are presented in Section VI. |
