Comput Methods Programs Biomed - Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation.

Tópicos

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Resumo

Electrocardiogram (ECG) based biometric matching suffers from high misclassification error with lower sampling frequency data. This situation may lead to an unreliable and vulnerable identity authentication process in high security applications. In this paper, quality enhancement techniques for ECG data with low sampling frequency has been proposed for person identification based on piecewise cubic Hermite interpolation (PCHIP) and piecewise cubic spline interpolation (SPLINE). A total of 70 ECG recordings from 4 different public ECG databases with 2 different sampling frequencies were applied for development and performance comparison purposes. An analytical method was used for feature extraction. The ECG recordings were segmented into two parts: the enrolment and recognition datasets. Three biometric matching methods, namely, Cross Correlation (CC), Percent Root-Mean-Square Deviation (PRD) and Wavelet Distance Measurement (WDM) were used for performance evaluation before and after applying interpolation techniques. Results of the experiments suggest that biometric matching with interpolated ECG data on average achieved higher matching percentage value of up to 4% for CC, 3% for PRD and 94% for WDM. These results are compared with the existing method when using ECG recordings with lower sampling frequency. Moreover, increasing the sample size from 56 to 70 subjects improves the results of the experiment by 4% for CC, 14.6% for PRD and 0.3% for WDM. Furthermore, higher classification accuracy of up to 99.1% for PCHIP and 99.2% for SPLINE with interpolated ECG data as compared of up to 97.2% without interpolation ECG data verifies the study claim that applying interpolation techniques enhances the quality of the ECG data.

Resumo Limpo

electrocardiogram ecg base biometr match suffer high misclassif error lower sampl frequenc data situat may lead unreli vulner ident authent process high secur applic paper qualiti enhanc techniqu ecg data low sampl frequenc propos person identif base piecewis cubic hermit interpol pchip piecewis cubic spline interpol spline total ecg record differ public ecg databas differ sampl frequenc appli develop perform comparison purpos analyt method use featur extract ecg record segment two part enrol recognit dataset three biometr match method name cross correl cc percent rootmeansquar deviat prd wavelet distanc measur wdm use perform evalu appli interpol techniqu result experi suggest biometr match interpol ecg data averag achiev higher match percentag valu cc prd wdm result compar exist method use ecg record lower sampl frequenc moreov increas sampl size subject improv result experi cc prd wdm furthermor higher classif accuraci pchip spline interpol ecg data compar without interpol ecg data verifi studi claim appli interpol techniqu enhanc qualiti ecg data

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