Multi-sensor fusion for robust computation of breathing rate

Abstract

Respiratory information can be obtained from the changes in electrical impedance across the chest, the electrocardiogram or the changes in light absorption across the finger. Running estimates of the breathing rate from each of these can be obtained from independent Kalman filters. A robust estimate of breathing rate is derived by fusing the outputs of these independent Kalman filters using a weighting calculated from the squared differences between each prediction from the filters and the corresponding measurements.