Adaptive filtering for suppression of respiratory artifact in impedance cardiography

Impedance cardiography is a noninvasive technique, based on sensing the variation in the electrical impedance of the thorax caused by variation in the blood volume during the cardiac cycle, for monitoring the stroke volume and some other cardiovascular indices. Respiratory and motion artifacts cause baseline drift in the sensed impedance waveform, particularly during or after exercise. This paper presents an LMS-based adaptive filtering technique for suppression of respiratory artifact for improving the estimation of the indices without smearing the beat-to-beat variations. It uses a reference signal, closely related to the respiratory artifact, obtained by a least-squares approximation based B-spline fitting on the contaminated impedance cardiogram in synchronism with the respiratory phases. The technique is evaluated on signals with simulated artifacts and on signals from nine healthy subjects and five patients with cardiovascular disorders. The values of the stroke volume, estimated on beat-to-beat basis, after suppression of respiratory artifact showed a good agreement with those from Doppler echocardiography.