Abstract: The present disclosure is directed towards systems and methods built for predictively timing the inflation and/or deflation of an intra-aortic balloon pump. A controller operates in three states: (1) initialization state, (2) learning state, and (3) peak detection state. The controller decomposes a patient's electrocardiogram signal to a power signal. It then learns characteristics of the patient's electrocardiogram signal during the learning state and computes adaptive threshold parameter values. During the peak detection state, the controller applies the learnt threshold parameter values on a current electrocardiogram signal to identify occurrence and timings of R peaks in the electrocardiogram signal. The R-to-R peak timings are then used to trigger inflation of an intra-aortic balloon pump.

Abstract: The present disclosure is directed towards systems and methods built for predictively timing the inflation and/or deflation of an intra-aortic balloon pump. A controller operates in three states: (1) initialization state, (2) learning state, and (3) peak detection state. The controller decomposes a patient's electrocardiogram signal to a power signal. It then learns characteristics of the patient's electrocardiogram signal during the learning state and computes adaptive threshold parameter values. During the peak detection state, the controller applies the learnt threshold parameter values on a current electrocardiogram signal to identify occurrence and timings of R peaks in the electrocardiogram signal. The R-to-R peak timings are then used to trigger inflation of an intra-aortic balloon pump.

Abstract: The present disclosure is directed towards systems and methods built for predictively timing the inflation and/or deflation of an intra-aortic balloon pump. A controller operates in three states: (1) initialization state, (2) learning state, and (3) peak detection state. The controller decomposes a patient's electrocardiogram signal to a power signal. It then learns characteristics of the patient's electrocardiogram signal during the learning state and computes adaptive threshold parameter values. During the peak detection state, the controller applies the learnt threshold parameter values on a current electrocardiogram signal to identify occurrence and timings of R peaks in the electrocardiogram signal. The R-to-R peak timings are then used to trigger inflation of an intra-aortic balloon pump.

Abstract: The present disclosure is directed towards systems and methods built for predictively timing the inflation and/or deflation of an intra-aortic balloon pump. A controller operates in three states: (1) initialization state, (2) learning state, and (3) peak detection state. The controller decomposes a patient's electrocardiogram signal to a power signal. It then learns characteristics of the patient's electrocardiogram signal during the learning state and computes adaptive threshold parameter values. During the peak detection state, the controller applies the learnt threshold parameter values on a current electrocardiogram signal to identify occurrence and timings of R peaks in the electrocardiogram signal. The R-to-R peak timings are then used to trigger inflation of an intra-aortic balloon pump.