Estimation of respiration from physiologic pressure signals

We created an algorithm to estimate the respiration signal, which consists of arterial blood pressure (ABP), and heart rate (HR) or RRI signals. Our goal is to create algorithmic models with which to estimate respiration by using signal processing and linear estimation. First, we created three algorithmic models: additive, amplitude modulation, and frequency modulation. Second, we used the output of those models as input for the linear estimator in order to estimate the original respiration input signal. The performance of the estimators was calculated to show their numeric results.