Realtime Monitoring of Vascular Conditions Using a Probabilistic Neural Network

This paper proposes a new method to discriminate the vascular conditions from biological signals by using a probabilistic neural network, and develops the diagnosis support system to judge the patient’s conditions on-line. For extracting vascular features including biological signals, we model the dynamic characteristics of an arterial wall by using mechanical impedance and estimate the impedance parameters “beat-to-beat”. As a result, this system can be utilized for the actual surgical operation, and the vascular conditions can be discriminated with high accuracy using the proposed method.