Classification of oscillometric envelope shape using frequent sequence mining
Classification of oscillometric envelope shape using frequent sequence mining is a scholarly work, published in 2013 in ''Annual International Conference of the IEEE Engineering in Medicine and Biology Society''. The main subjects of the publication include pattern recognition, data mining, blood pressure, arterial hypertension, computer science, artificial intelligence, oscillometry, closing, sequence mining, vascular stiffness, diastole, radar envelope, mathematics, algorithm, and heart rate variability. The study proposes a novel shape classification method that uses data mining techniques to determine the characteristic sequences for different envelope shapes.