A novel compressed sensing method using specific dictionaries for ECG waveforms demonstrates feasibility for signal reconstruction and classification.
Computational validation supports technical feasibility; leaves open clinical applicability in ECG monitoring.
The paper presents a new method and results regarding the compressed sensing (CS) and classification of ECG waveforms using a general dictionary as well as specific dictionaries built using normal and pathological cardiac patterns. The proposed method has been validated by computation of the distortion errors between the original and the reconstructed signals and by the classification ratio of the reconstructed signals obtained with the k-nearest neighbors (KNN) algorithm.
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Fira et al. (2012) studied this question.
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