engleski

A Compressive Sensing Approach for ECG Classification

This paper addresses the problem of ECG signal variability using the theory of compressive sensing. Compressive sensing provides a novel framework for representing sparse or compressible signals, with a significantly reduced set of measurements than that needed by Nyquist rate and it can be implemented for cardiac arrhythmia detection. Furthermore, the paper applies random forest algorithm for reliable automatic classification of ECG signals.

ECG; compressive sensing; random forest

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