A discriminant-analysis-based suction detection system for rotary blood pumps

A new suction detection system for rotary blood pumps used in left ventricular assist devices is presented. The system can correctly classify pump flow patterns, based on a discriminant analysis (DA) model that combines several indices derived from the pump flow signal to make a decision about the pump status. The indices considered in this approach are frequency-, time-, and time-frequency-domain indices. The frequency-domain indices detect changes in the harmonic and subharmonic energy content of the pump flow signal when a suction event is occurring. The time-domain indices detect changes in pump flow pulsatility based on a beat-to-beat analysis of the pump flow and first derivative of pump flow. The time-frequency index can track variations in the standard deviation of the instantaneous frequency of the pump flow signal. These indices are combined in a DA decision system to generate a suction alarm. The proposed system has been tested in simulations and in-vivo experimental tests and produced satisfactory results