Key result
Artificial Neural Networks estimating blood pressure from PPG signals showed better accuracy than linear regression, satisfying the American National Standards of the AAMI.
Why the study?
Does an Artificial Neural Network-based method improve the accuracy of continuous blood pressure estimation from a PPG signal compared to linear regression?
Population
Data extracted from the Multiparameter Intelligent Monitoring in Intensive Care waveform database, analyzing…
Comparison
Artificial Neural Networks for estimating blood… vs Linear regression method
Authors
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May enable cuffless continuous BP monitoring; leaves open prospective clinical validation.
Does an Artificial Neural Network-based method improve the accuracy of continuous blood pressure estimation from a PPG signal compared to linear regression?
An Artificial Neural Network-based method can accurately estimate continuous blood pressure from PPG signals, outperforming linear regression and meeting AAMI standards.
Kurylyak et al. (2013) studied Blood pressure estimation. Artificial Neural Networks (ANNs) vs. Linear regression method was evaluated on Accuracy of blood pressure estimation compared to reference values. Artificial Neural Networks estimating blood pressure from PPG signals showed better accuracy than linear regression, satisfying the American National Standards of the AAMI.
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