Assessment of the stability of morphological ECG features and their potential for person verification/identification
| Autor: | Ivaylo Christov, Vessela Krasteva, Giovanni Bortolan, Irena Jekova, Dimitar Simov, Mikhail Matveev, Nikolay Mudrov |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
business.industry Speech recognition Pattern recognition Regression analysis Stability (probability) Regression Coincidence Correlation 03 medical and health sciences QRS complex 030104 developmental biology 0302 clinical medicine Amplitude lcsh:TA1-2040 Feature (computer vision) 030220 oncology & carcinogenesis Artificial intelligence lcsh:Engineering (General). Civil engineering (General) business |
| Zdroj: | MATEC Web of Conferences, Vol 125, p 02004 (2017) |
| ISSN: | 2261-236X |
| DOI: | 10.1051/matecconf/201712502004 |
| Popis: | This study investigates the potential of a set of ECG morphological features for person verification/identification. The measurements are done over 145 pairs of ECG recordings from healthy subjects, acquired 5 years apart (T1, T2 = T1+5 years). Time, amplitude, area and slope descriptors of the QRS-T pattern are analysed in 4 ECG leads, forming quasi-orthogonal lead system (II&III, V1, V5). The correspondence between feature values in T1 and T2 is verified via factor analysis by principal components extraction method; correlation analysis applied over the measurements in T1 and T2; synthesis of regression equations for prediction of features’ values in T2 based on T1 measurements; and cluster analysis for assessment of the correspondence between measured and predicted feature values. Thus, 11 amplitude descriptors of the QRS complex are highlighted as stable, i.e. keeping their strong correlation (≥0.7) within a certain factor, weak correlation ( |
| Databáze: | OpenAIRE |
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