Key result
An automatic Premature Ventricular Contraction detection method using photoplethysmographic signals achieved sensitivities of 96.05% and 95.37% and specificities of 99.85% and 99.80% for two PVC types.
Why the study?
Does an automatic detection method using PPG signals accurately detect Premature Ventricular Contractions compared to ECG?
Does an automatic detection method using PPG signals accurately detect Premature Ventricular Contractions compared to ECG?
An Artificial Neural Network-based algorithm using PPG signals can reliably detect premature ventricular contractions with high sensitivity and specificity.
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PPG-based PVC detection warrants wearable algorithm development; leaves open clinical adoption pending prospective ECG validation.
Sološenko et al. (2014) studied Premature Ventricular Contraction. Automatic PVC detection and classification method using PPG signals vs. Synchronously registered ECG signals was evaluated on Sensitivity and specificity for PVC detection. An automatic Premature Ventricular Contraction detection method using photoplethysmographic signals achieved sensitivities of 96.05% and 95.37% and specificities of 99.85% and 99.80% for two PVC types.
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