Probabilistic estimation of respiratory rate using Gaussian processes
| Autor: | Pimentel, MAF, Clifton, DA, Clifton, L, Tarassenko, L, IEEE |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Adult
Male Covariance function Respiratory rate Computer science Normal Distribution symbols.namesake Electrocardiography Young Adult Respiratory Rate Statistics medicine Supine Position Waveform Humans cardiovascular diseases Gaussian process Aged Probability Analysis of covariance Aged 80 and over medicine.diagnostic_test Estimation theory business.industry Respiration Probabilistic logic Age Factors Reproducibility of Results Pattern recognition Signal Processing Computer-Assisted Middle Aged Models Theoretical symbols Regression Analysis Female Artificial intelligence business Algorithms |
| Zdroj: | EMBC |
| ISSN: | 2694-0604 |
| Popis: | The presence of respiratory information within the electrocardiogram (ECG) signal is a well-documented phenomenon. We present a Gaussian process framework for the estimation of respiratory rate from the different sources of modulation in a single-lead ECG. We propose a periodic covariance function to model the frequency- and amplitude-modulation time series derived from the ECG, where the hyperparameters of the process are used to derive the respiratory rate. The approach is evaluated using data taken from 40 healthy subjects each with 2 hours of monitoring, containing ECG and respiration waveforms. Results indicate that the accuracy of our proposed method is comparable with that of existing methods, but with the advantages of a principled probabilistic approach, including the direct quantification of the uncertainty in the estimation. © 2013 IEEE. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|