Improved respiration rate estimation using a Kalman filter and wavelet cross-coherence

Introduction: Respiration rate is a common measurement in the intensive care unit (ICU) which is well correlated with patient severity. However, automated estimation of the respiration rate, especially when the patient is not intubated, is prone to large errors. Here we present a method of merging respiration estimates from the electrocardiogram (ECG) merged based on a novel signal quality index.