Key result
The proposed Ensemble Empirical Mode Decomposition algorithm efficiently extracted respiratory information from PPG signals with a 97% average accuracy, overcoming drawbacks of traditional EMD methods.
The proposed EEMD algorithm can accurately extract respiratory rate from PPG signals, potentially eliminating the need for additional respiratory sensors.
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May enable combined cardiorespiratory monitoring from single PPG; hypothesis-generating pending prospective clinical validation.
Mitali et al. (2015) studied this question. Ensemble Empirical Mode Decomposition algorithm vs. traditional EMD method was evaluated on Average accuracy of extracting respiratory information. The proposed Ensemble Empirical Mode Decomposition algorithm efficiently extracted respiratory information from PPG signals with a 97% average accuracy, overcoming drawbacks of traditional EMD methods.
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