In this paper we address the acceleration of the Hermite function
characterization of the heartbeat by means of massively parallel Graphics Processing
Units. This characterization can be used to develop tools to help the cardiologist to
study and diagnose heart disease. However, obtaining this characterization,
especially when a large number of functions is used to achieve a high accuracy in
heartbeat representation, is very resource intensive. This paper addresses off-line
and on-line heartbeat characterization, assessing the acceleration capabilities of
Graphics Processing Units for these tasks. Polynomials up to the 30th order are used
in the study. The results yield that the off-line processing of long electrocardiogram
recordings with a GPU can be computed up to 186 faster than a standard CPU,
while real-time processing can be up to 110x faster.
Keywords: Electrocardiogram, Hermite polynomials, graphics processing unit, CUDA, arrhythmia, clustering.
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