Research On Intelligent Control System Of Medical Air Cushion Garment

At present,our country is in the age of aging,more and more people cannot carry out normal daily activities because of fracture,stroke and other reasons.Long-term bedridden patients are prone to muscle atrophy and degeneration,deep venous thrombosis and other complications.Conventional massage nursing method cannot be satisfied because of its large amount of human and material resources consumption.The emergence of air cushion garment for inflatable massage overcomes the timeconsuming and energy-consuming problems of routine massage nursing to a certain extent.However,due to the single function of air cushion apparel products on the market at present,the air bag can only be filled regularly and quantitatively.If the pressure is not set properly,it is very likely to cause secondary injury to patients.Therefore,on the basis of existing air cushion garments,this thesis studies the problem of automatic adjustment of air bag pressure.Aiming at the conventional open-loop inflatable mode,a double-closed-loop intelligent control system based on heart rate change to adjust the pressure in the air bag was designed.The system is mainly divided into inner ring pressure control part and outer ring pressure setting value adjustment part.For the pressure control part of the inner ring,the first-order inertial mathematical model with time delay of the airbag is obtained through mechanism deduction and experimental verification.On the basis of using Smith predictive control method to solve the problem of time delay,aiming at the problem of small range variation of actual model parameters,an auxiliary low-pass filter is added to the main feedback channel,and a method of modifying filter parameters in the feedback channel based on fuzzy adaptive is designed.The simulation results show that when the model cannot match perfectly in pressure control,compared with conventional PID control and Smith control,the system output overshoot is smaller and the adjustment time is faster.For the adjusting part of the outer ring pressure setting value,the methods of determining the initial pressure setting value according to the patient's physiological information and adjusting the pressure setting value according to the patient's heart rate change are proposed.The initial pressure setting value was determined by BP neural network and six individual indices such as patient's sex and age.In the training process of BP network,the improved variable probability genetic algorithm is used to optimize the BP network,which avoids the problems of slow convergence and low classification accuracy caused by falling into local minimum.The adjustment of pressure setting value is based on the heart rate and heart rate change rate of patients,which is realized by fuzzy reasoning.The simulation results show that the double closed-loop control system proposed in this thesis can adjust the pressure in the air bag based on the change of heart rate.The adjustment strategy of the pressure setting value adjustment part is close to the manual pressure adjustment process.The inner pressure control part can also make the actual pressure stable,fast and accurately follow the change of the pressure setting value,which lays a theoretical foundation for the development and application of intelligent medical air cushion garment.