Title :
An intelligent control of Blood Pressure system using PID and Neural Network
Author :
Elamvazuthi, I. ; Aymen, O.M. ; Salih, Yasir ; Tawfeig, Huzaifa
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. Technologi PETRONAS, Tronoh, Malaysia
Abstract :
This paper presents an intelligent control approach for Blood Pressure (BP) system using PID-Neural Network (PIDNN). This paper discusses the use of PIDNN to optimize the regulation of Mean Arterial Pressure (MAP) through the infusion of Sodium Nitroprusside (SNP). Multi-layer Perception (MLP) is used as Neural Network pattern predictor. Simulation studies based on a sensitive model of MAP shows that the proposed approach is able provide a good performance.
Keywords :
blood vessels; drug delivery systems; drugs; haemodynamics; intelligent control; medical computing; medical control systems; multilayer perceptrons; pattern recognition; sodium compounds; MAP sensitive model; Na2[Fe(CN)5NO]-H2O; PID-Neural Network; PIDNN; blood pressure system; intelligent control approach; mean arterial pressure; multilayer perception; neural network pattern predictor; simulation study; sodium nitroprusside infusion; Biomedical monitoring; Blood pressure; Conferences; Drugs; Mathematical model; Monitoring; Neural networks; Blood Pressure Control; Infusion Rate; Mean Arterial Pressure (MAP); Multilayer Perceptron (MLP); PID-Neural Network; Sodium Nitroprusside;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2013 8th IEEE Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-6320-4
DOI :
10.1109/ICIEA.2013.6566522
