Respiratory rate detection algorithms by photoplethysmography signal processing

Annu Int Conf IEEE Eng Med Biol Soc. 2008:2008:1140-3. doi: 10.1109/IEMBS.2008.4649362.

Abstract

Photoplethysmography (PPG) offers the clinically meaningful parameters, such as, heart rate, and respiratory rate. In this study, we presented three respiratory signal detection algorithms using photoplethysmography raw data generated from commercial PPG sensor: (1)Min-Max (2)Peak-to-Peak (3)Pulse Shape. As reference signal, nasal sensor signal was acquired simultaneously and compared and analyzed. We used two types of moving average filtering technique to process three PPG parameters. In laboratory experiment, 6 subjects' PPG signals were measured when they respire ten and fifteen, and arbitrary times per minute. From the results, following conclusions were drawn. Min-Max and Peak-to-Peak algorithms perform better than Pulse shape algorithm. They can be used to detect respiratory rate. But, Pulse Shape algorithm was accurate for subject 4 only. More experimental data is necessary to improve the accuracy and reliability.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Diagnosis, Computer-Assisted / methods*
  • Humans
  • Oscillometry / methods*
  • Photoplethysmography / methods*
  • Reproducibility of Results
  • Respiratory Mechanics / physiology*
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted*