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Updated: Jun 12, 2025
Semi-automated Optical Heartbeat Analysis of Small Hearts
Published on: September 16, 2009
Automatic Classification of Anomalous ECG Heartbeats from Samples Acquired by Compressed Sensing
Enrico Picariello1, Francesco Picariello1, Ioan Tudosa1
1Department of Engineering, University of Sannio, 82100 Benevento, Italy.
Abstract:
In this paper, a method for the classification of anomalous heartbeats from compressed ECG signals is proposed. The method operating on signals acquired by compressed sensing is based on a feature extraction stage consisting of the evaluation of the Discrete Cosine Transform (DCT) coefficients of the compressed signal and a classification stage performed by means of a set of k-nearest neighbor ensemble classifiers. The method was preliminarily tested on five classes of anomalous heartbeats, and it achieved a classification accuracy of 99.40%.
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