Computational Physiology and Clinical Inference Group

The Computational Physiology and Clinical Inference Group (CPCI) develops and applies computational models of human physiology for clinical monitoring and inference. Current research focuses on cardiovascular, cerebrovascular, respiratory and neurological applications.

The overarching objectives of the research in the CPCI Group are to enhance patient monitoring, improve clinical decision making, and better understand physiological and pathophysiological processes. We develop and use mathematical models derived from physiology, along with signal processing and estimation methods, to extract relevant information from clinical data. The models provide the constraints that allow readily observable data streams (such as waveforms of ECG, arterial blood pressure, cerebral blood flow velocity, near-infrared transmission through cerebral tissue, and/or EEG) to be related to physiological variables and parameters that are unmeasured but more directly reflective of changes in pathological state (quantities such as cardiac output, cardiac contractility and ejection fraction, peripheral resistance, intracranial pressure, cerebral metabolism and/or seizure activity). The models thereby form the basis for estimation of unmeasured quantities from measured ones, thus enabling a fuller assessment and tracking of patient state, and a more comprehensive description of the underlying physiology.