title: Extracting a cardiac signal from the extracorporeal pressure sensors of a hemodialysis machine.
abstract: 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.
authors.forename: Mattias
authors.initials: M
authors.lastname: Holmer
authors.forename: Frida
authors.initials: F
authors.lastname: Sandberg
authors.forename: Kristian
authors.initials: K
authors.lastname: Solem
authors.forename: Egle
authors.initials: E
authors.lastname: Grigonyte
authors.forename: Bo
authors.initials: B
authors.lastname: Olde
authors.forename: Leif
authors.initials: L
authors.lastname: Sörnmo
mesh_terms: D001794:Blood Pressure / Q000502:physiology*; D001795:Blood Pressure Determination; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D006435:Renal Dialysis / Q000295:instrumentation* / Q000379:methods; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*