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                <term xml:lang="en">P-wave morphology</term>
                <term xml:lang="en">atrial fibrillation risk detection</term>
                <term xml:lang="en">body surface ECG</term>
                <term xml:lang="en">clustering algorithm</term>
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              <p>The recognition of patients with atrial fibrillation (AF) risk, from body surface ECG, remains an actual problem. The aim of the work is to investigate how the study of the P-wave morphology may assess any clustering algorithm in separating patients with AF risk from healthy subjects. The clustering is done by the k-means algorithm and using a new method: the integrated shape averaging (ISA). According to the results, the method was able to separate patients with AF risk from safety ones with 75 % sensitivity and 70 % specificity on 40 recordings. Furthermore, two families of P-wave patterns were characterized among the patients with AF risk and probably corresponding to electrical manifestations of conduction defects in the left or the right atrium.</p>
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