Rate-responsive pacing using the atrio-ventricular conduction time: design and test of a new algorithm.
The cardio-circulatory system of chronotropic incompetent patients is unable to adapt heart rate adequately to the level of strain. A common therapy is the implantation of a pacemaker that stimulates the heart at a rate derived from a strain related sensor signal. The paper describes a new pacemaker concept that uses a well-defined time interval in the electrogram as a sensor parameter, the atrioventricular conduction time (AVCT). Identification experiments with patients delivered the stationary and dynamic behaviour of AVCT subject to variations in the exercise rate and the pacing frequency. Furthermore, it was demonstrated that AVCT is perturbed by respiratory activity. The new rate-responsive algorithm, which uses the internal model control principle, explicitly takes into account the closed-loop nature of the underlying system. The major design objectives were: extended range of the individual heart rate; effective attenuation of the respiratory-related disturbance; and stability. Seven patients undergoing incremental exercise were paced with this AVCT-based algorithm. The experiments confirmed the suitability of this concept with respect to the design goals. The patients' peak intrinsic heart rate at exercise was 100 +/- 20min(-1). When paced with the AVCT algorithm, the paced heart rate was 126 +/- 12min(-1). The increase was significant (26 +/- 13min(-1); 15 to 53 min(-1)), which clearly demonstrated the potential of this concept to restore chronotropic competence.
Hexamer
M
M
Department of Biomedical Engineering, Medical Faculty, Ruhr University, Bochum Germany. hexamer@biomed.rub.de
Drewes
C
C
Meine
M
M
Kloppe
A
A
Weckmüller
J
J
Mügge
A
A
Werner
J
J
D000368:Aged; D000465:Algorithms; D001283:Atrioventricular Node / Q000503:physiopathology*; D002304:Cardiac Pacing, Artificial / Q000379:methods*; D004562:Electrocardiography / Q000379:methods; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012804:Sick Sinus Syndrome / Q000503:physiopathology / Q000628:therapy*; D012815:Signal Processing, Computer-Assisted