Abstract
A new tool for characterizing systemic and local hemodynamic behavior in real-time has been developed. Through the evaluation of two peripheral circulatory waveform measurements (e.g. continuous measurements such as pressure or flow or volumetric change) this new signal-processing algorithm generates two compact, low order models that describe the distinct branch dependent features of the measured circulatory signals. The method employs a multichannel blind system identification (MBSI) technique that has been reformulated to use a Laguerre basis series expansion. The new MBSI approach allows accurate identification of vascular hemodynamics in experimental data measured in a swine model.
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