Estimation of the respiratory component from ballistocardiography signal using adaptive interference cancellation

Currently real-time heart rate and respiration monitoring is considered of major importance to be applied in the hospital and eventually at home. A new method for extracting respiratory signal from ballistocardiography, which is a completely non-invasive and unconstrained heart rate measurement method, is presented. We developed a system to detect ballistocardiography signal without subject´s awareness. And then the adaptive interference cancellation algorithm, which is able to enhance the common information and attenuate the uncorrelated noise, is applied to derive respiration component. This method was verified using about 1040 sets of 1-min long data collected from 20 healthy subjects. The ECG and nasal thermistor signals were recorded simultaneously as reference signal. The results showed that, compared with the reference data, the extracted pulse waveform was synchronized and the average error rate of quantitative assessment was feasible. The study shows that respiration can be derived under dynamic activities from ballistocardiography signal without significant differences from traditional methods.