Key result
Synthetic fuzzy logic controller maintains optimal coupling conditions during continuous noninvasive blood pressure monitoring.
Why the study?
Accurate noninvasive continuous blood pressure waveform monitoring requires maintaining optimal coupling condition, but mean arterial pressure cannot be measured directly, posing a control challenge.
The proposed model-based synthetic fuzzy logic controller offers a novel engineering approach to maintain optimal coupling for noninvasive continuous blood pressure monitoring.
In this paper, a new measurement system for the noninvasive 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 registers 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 estimates the MAPs changing tendency based on the identified arterial pressure-volume model.
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Wang et al. (2002) studied Blood pressure monitoring. Model-based synthetic fuzzy logic controller was evaluated. A model-based synthetic fuzzy logic controller was designed to compensate for changes in mean arterial pressure to maintain optimal coupling conditions for noninvasive blood pressure monitoring.
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