A Comparative Analysis of DBSCAN, K-Means, and Quadratic Variation Algorithms for Automatic Identification of Swallows from Swallowing Accelerometry Signals

Abstract

Background Cervical auscultation with high resolution sensors is currently under con-sideration as a method of automatically screening for specific swallowing ab-normalities. To be clinically useful without human involvement, any devices based on cervical auscultation should be able to detect specified swallowing events in an automatic manner. Methods In this paper, we comparatively analyze the density-based spatial clus-tering of applications with noise algorithm (DBSCAN), a k-means based algorithm, and an algorithm based on quadratic variation as methods of differentiating periods of swallowing activity from periods of time withou