Premature Ventricular Contraction Recognition Based on a Deep Learning Approach

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Features</td><td class="align_center">Explanation</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">SDSD</td><td class="align_center">Standard deviation of dissimilarities among sequential RR intervals.</td></tr><tr><td class="align_left">Ratio</td><td class="align_center">Ratio=(maxRR −minRR)/<i>μ</i>rr</td></tr><tr><td class="align_left">rMSSD</td><td class="align_center">Square root of the mean of the squares of dissimilarities among neighboring RR intervals.</td></tr><tr><td class="align_left">SDRR</td><td class="align_center">Standard deviation of all RR intervals</td></tr><tr><td class="align_left">pRR10</td><td class="align_center">Percentage of dissimilarities among neighboring RR intervals that are greater than 10 ms.</td></tr><tr><td class="align_left">pRR50</td><td class="align_center">Percentage of dissimilarities among neighboring RR intervals that are greater than 50 ms.</td></tr><tr><td class="align_left">MeanRR</td><td class="align_center">Mean value of all RR intervals (<i>μ</i>)</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Explanation of statistical features.</div>

Journal of Healthcare Engineering

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Table 1

Table 1: Premature Ventricular Contraction Recognition Based on a Deep Learning Approach 