Respiratory Rate Monitoring Based On Photoplethysmography

Respiration is a physiological process to keep the ordinary life and function, which gasexchange between the human body and external environment. Respiratory rate is a veryimportant physiological parameter to monitor during some health care occasions.Respiratory function interacts with cardiopulmonary function, so it is of great significancefor the diagnosis and treatment of some respiratory related diseases. Now the mainapplication field of respiratory monitoring rate is in clinical environment in hospital. Thedirect detection is a major method to monitor respiratory rate, such as impedance methods.But with the advancement of science and technology and the development of society,people want to make it happen next in the family portable monitoring and hope theequipment is as simple as possible. Photoplethysmography is a kind of pulse waveformwhich measures through photoelectric sensor and is rich in human physiologicalinformation. We can get accurate photoplethysmography easily from common oxygensaturation probe. So it is of great importance to extract respiratory rate fromphotoplethysmography.On the basis of existing research of photoplethysmography, this paper presents analgorithm based on characteristic parameter extraction for monitoring respiratory rate fromphotoplethysmography. First, the photoplethysmography signal go through a low-pass filterto remove the power-line interference and other high frequency disturb. Recognizing pulsewaveform from PPG using a recognition algorithm; Then, extracting characteristicparameters from the recognized pulse waveform, according to the characteristic parameterestablishing four sequences of envelope, interval, amplitude and area. These four sequencesare resampled by interpolation. Respectively, applying chirp z transform to analysis thespectral spectrum of the resampled signals to extract frequency information of the foursignals; Finally, the respiratory rate is obtained from the weighted average of all the fourfrequency values. The algorithm are verified with the data from the database. The resultsshow that the method we presented can extracte respiratory rate fromphotoplethysmography accurately and reliably. It has its practical value in using in portableand home monitoring.The detection of obstructive sleep apnea based on oxygen saturation andphotoplethysmography. Analysing the relationship between photoplethysmography, oxygen saturation and obstructive sleep apnea. Detecting obstructive sleep apnea according todesaturation and the amplitude, upper envelope, lower envelope of photoplethysmography,which lays the theoretical foundation for monitoring sleep status usingphotoplethysmography.