Mattias Holmer

Extracting a Cardiac Signal From the Extracorporeal Pressure Sensors of a Hemodialysis Machine

Although patients undergoing hemodialysis treatment often suffer from cardiovascular disease, monitoring of cardiac rhythm is not performed on a routine basis. Without requiring any extra sensor, this study proposes a method for extracting a cardiac signal from the built-in extracorporeal venous pressure sensor of the hemodialysis machine. The extraction is challenged by the fact that the cardiac component is much weaker than the pressure component caused by the peristaltic blood pump. To further complicate the extraction problem, the cardiac component is difficult to separate when the pump and heart rates coincide. The proposed method estimates a cardiac signal by subtracting an iteratively refined blood pump model signal from the signal measured at the extracorporeal venous pressure sensor. The method was developed based on simulated pressure signals, and evaluated on clinical pressure signals acquired during hemodialysis treatment. The heart rate estimated from the clinical pressure signal was compared to that derived from a photoplethysmographic reference signal, resulting in a difference of 0.07 ± 0.84 beats/min. The accuracy of the heartbeat occurrence times was studied for different strengths of the cardiac component, using both clinical and simulated signals. The results suggest that the accuracy is sufficient for analysis of heart rate and certain arrhythmias.

Cardiac signal estimation based on the arterial and venous pressure signals of a hemodialysis machine

Continuous cardiac monitoring is usually not performed during hemodialysis treatment, although a majority of patients with kidney failure suffer from cardiovascular disease. In the present paper, a method is proposed for estimating a cardiac pressure signal by combining the arterial and the venous pressure sensor signals of the hemodialysis machine. The estimation is complicated by the periodic pressure disturbance caused by the peristaltic blood pump, with an amplitude much larger than that of the cardiac pressure signal. Using different techniques for combining the arterial and venous pressure signals, the performance is evaluated and compared to that of an earlier method which made use of the venous pressure only. The heart rate and the heartbeat occurrence times, determined from the estimated cardiac pressure signal, are compared to the corresponding quantities determined from a photoplethysmographic reference signal. Signals from 9 complete hemodialysis treatments were analyzed. For a heartbeat amplitude of 0.5 mmHg, the median absolute deviation between estimated and reference heart rate was 1.3 bpm when using the venous pressure signal only, but dropped to 0.6 bpm when combining the pressure signals. The results show that the proposed method offers superior estimation at low heartbeat amplitudes. Consequently, more patients can be successfully monitored during treatment without the need of extra sensors. The results are preliminary, and need to be verified on a separate dataset.

Heart rate estimation from dual pressure sensors of a dialysis machine

Dialysis patients often suffer from cardiovascular diseases, motivating the use of continuous monitoring of cardiac activity in clinical routine. Cardiac pressure pulses propagate through the vascular system and enter the extracorporeal blood circuit of a dialysis machine, where the pulses are captured by pressure sensors. The cardiac pulses are obscured by the much stronger pressure pulses originating from the peristaltic blood pump. We have previously shown that a cardiac signal can be extracted from the venous pressure signal. However, that method has been found to perform less well at very low cardiac pressure pulse amplitudes. In the present study, we propose a novel method which addresses this issue by using the signals from both the arterial and the venous pressure sensors. The method is compared to the previous method on clinical data using a photoplethysmogram as reference. The results suggests that heart rate can be estimated more accurately from pressure signals with lower cardiac signal amplitude when both arterial and venous pressure are used, compared to when only the venous signal is used.