Model-based synthetic fuzzy logic controller for indirect blood pressure measurement

In this paper, a new measurement system for the non-invasive monitoring of the continuous blood pressure waveform in the radial artery is presented. The proposed system comprises a model-based fuzzy logic controller, an arterial tonometer and a micro syringe device. The flexible diaphragm tonometer is to register the continuous blood pressure waveform. To obtain accurate measurement without distortion, the tonometer's mean chamber pressure must be kept equal to the mean arterial pressure (MAP), the so-called optimal coupling condition, such that the arterial vessel has the maximum compliance. Since the MAP cannot be measured directly, to keep the optimal coupling condition becomes a tracking control problem with unknown desired trajectory. To solve this dilemma, a model-based fuzzy logic controller is designed to compensate the change of MAP by applying a counter pressure on the tonometer chamber through the micro syringe device. The proposed controller consists of a model-based predictor and a synthetic fuzzy logic controller (SFLC). The model-based predictor is to estimate the MAPs changing tendency based on the identified arterial pressure-volume model. The SFLC is composed of three subcontrollers, each of which is a simple fuzzy logic controller, for processing the three changing states of the MAP: ascending, descending and stabilizing states, respectively. Simulation results show that, for the MAP with changing rates of +/-10, +/-20 or +/-30 mm Hg/min, the model-based SFLC can beat-to-beat adjust the tonometer's chamber pressure only with a mean square error of 1.9, 2.2, or 2.8 nun Hg, respectively.