Key result
The proposed electrocardiogram quality evaluation algorithm based on signal mobility factors achieved an accuracy of 93.40% on the PhysioNet Computing in Cardiology challenge 2011 test dataset.
Population
Test dataset provided by the PhysioNet Computing in Cardiology (CinC) challenge 2011
Authors
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May support automated ECG quality assessment in research; leaves open prospective clinical validation before adoption.
A novel ECG signal quality assessment algorithm based on signal mobility factors demonstrated high accuracy (93.40%) on a standard challenge dataset.
Naseri et al. (2013) studied Electrocardiogram (ECG) signal quality assessment. Expert electrocardiogram quality evaluation algorithm based on signal mobility factors was evaluated on Accuracy of binary quality assessment (accept-reject). The proposed electrocardiogram quality evaluation algorithm based on signal mobility factors achieved an accuracy of 93.40% on the PhysioNet Computing in Cardiology challenge 2011 test dataset.
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