A Real-Time Dual Heart and Respiratory Rate Estimator for Electrical Impedance Tomography

Thoracic electrical impedance tomography provides a non-invasive signal that combines changes from both cardiac and respiratory events. Heart and respiratory rates are important physiological parameters to diagnose and monitor cardiorespiratory conditions, and necessary for further more sophisticated analyses. We propose a real-time, model-based approach in the time domain to estimate both heart and respiratory rates simultaneously from the electrical impedance tomography signal. We tested our method using simulated non-stationary signals with varying relative cardiac and respiratory contributions. Our method could accurately estimated heart and respiratory rates with root mean square errors as low as 0.54 and 0.86 cycles per minute, and Bland-Altman biases as low as 0.04 +/- 1.04 and -0.07 +/- 1.53 cycles per minute, respectively. Additionally, the algorithm ran in real-time with or without parallelization, reaching computation times of 10 +/- 1.1 ms.