Key result
A novel autoregressive modelling technique for extracting breathing rate from the photoplethysmogram outperformed existing techniques, with a mean error of 0.04 breaths per minute.
Population
Consistent data set of photoplethysmogram (PPG) waveforms
Comparison
Novel technique using autoregressive modelling… vs Various existing methods for extracting…
Design
Other
Authors
Loading...
May enable continuous respiratory monitoring via routine PPG; hypothesis-generating and requires prospective validation before clinical use.
A novel autoregressive modelling technique for extracting breathing rate from PPG waveforms demonstrates high accuracy with a mean error of 0.04 breaths per minute.
Susannah G. Fleming Lionel Tarassenko (2007) studied this question. Autoregressive modelling technique vs. Existing signal processing techniques was evaluated on Mean error in breathing rate. A novel autoregressive modelling technique for extracting breathing rate from the photoplethysmogram outperformed existing techniques, with a mean error of 0.04 breaths per minute.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: