摘要：AbstractCardiac driver functions, used to model elastance changes that drive heart contraction, have significance both in the context of larger models and independently as a means of deriving important metrics such as the End Systolic Pressure Volume Relationship (ESPVR). This paper describes an approach for deriving the driver function on a beat-to-beat basis using a combination of strong correlations (R > 0.97) to readily measured aortic pressure waveform features and population constants assessed across a development cohort of 3 porcine specimens (62350 heartbeats). This approach was then validated over an independent test cohort of 4 porcine specimens (54410 heartbeats) and found to decrease the normalised area-under-the-curve error to a median of 18.0% compared to 41.0% when using only population constant values. This approach has the potential to provide further, real-time, patient specific information about the internal dynamics of the heart without requiring additional, invasive instrumentation of patients.
关键词：KeywordsBiological and medical system modellingCardiovascular systemDecision support systems
