Numerical simulation of volume-controlled mechanical ventilated respiratory system with 2 different lungs

Numerical modeling and development of a dual lung simulator using partitioned fluid-structure interaction approach for ventilator testing

New designs of mechanical ventilators require extensive testing before utilizing the ventilator on a patient. Test lungs are commonly used to understand the behavior of new designs of ventilators and the lung mechanics. The current study aims to develop a numerical model of dual test lungs utilizing the partitioned fluid-structure interaction (FSI) approach and test it against the available experimental data of volume-controlled ventilation. Two breathing rates of 12 and 18 bpm were studied at two different tidal volumes of 500 and 600 ml for spontaneous breathing. It is found that with an increase in the compliance (tidal volume/pressure rise) of the lung, the peak pressure rise inside the test lung decreases irrespective of the breathing rate. The maximum average pressure of 44.73, 27.45, and 14 cm H₂ O is observed for static lung compliances of 10, 21 , and 39 ml/cm H₂ O, respectively at a tidal volume of 600 ml. Similarly, the maximum von-misses stress was higher (498 kPa) for the lung with lower compliance (10 ml/cm H₂ O) as compared to the lung with higher compliance (39 ml/cm H₂ O) at the end of inspiration. This study forms a basis for using computational methods to model simple lung simulators that can effectively investigate the lung mechanics for both spontaneous and ventilated breathing. Thus, it can be utilized as a reference to test novel designs of mechanical ventilators.

Advanced mechanical ventilation modes: design and computer simulations

In this paper, three different advanced mechanical ventilation modes, pressure regulated volume control ventilation (PRVC), proportional assist ventilation (PAV), and adaptive support ventilation (ASV) are designed and simulated on the computer via MATLAB/Simulink. In the algorithms of advanced ventilation modes, a closed-loop control structure is used and recursive least squares method is considered for the estimation of respiratory mechanics. The designed algorithms are then applied to the human respiratory system model for the active and/or passive patient cases. Simulation results show that such algorithms can be designed and simulated on the computer successfully. In addition, the simulation environment helps us to understand the working principles of the advanced modes and to see the results such as ventilator waveforms, the effect of the parameter changes. Moreover, it also allows us to improve and test the algorithms and strategies quickly and efficiently.

A Lung Sound Category Recognition Method Based on Wavelet Decomposition and BP Neural Network

In this paper, a method of characteristic extraction and recognition on lung sounds is given. Wavelet de-noised method is adopted to reduce noise of collected lung sounds and extract wavelet characteristic coefficients of the de-noised lung sounds by wavelet decomposition. Considering the problem that lung sounds characteristic vectors are of high dimensions after wavelet decomposition and reconstruction, a new method is proposed to transform the characteristic vectors from reconstructed signals into reconstructed signal energy. In addition, we use linear discriminant analysis (LDA) to reduce the dimension of characteristic vectors for comparison in order to obtain a more efficient way for recognition. Finally, we use BP neural network to carry out lung sounds recognition where comparatively high-dimensional characteristic vectors and low- dimensional vectors are set as input and lung sounds categories as output with a recognition accuracy of 82.5% and 92.5%.

Evolutionary Algorithm-Based Friction Feedforward Compensation for a Pneumatic Rotary Actuator Servo System

The friction interference in the pneumatic rotary actuator is the primary factor affecting the position accuracy of a pneumatic rotary actuator servo system. The paper proposes an evolutionary algorithm-based friction-forward compensation control architecture for improving position accuracy. Firstly, the basic equations of the valve-controlled actuator are derived and linearized in the middle position, and the transfer function of the system is further obtained. Then, the evolutionary algorithm-based friction feedforward compensation control architecture is structured, including that the evolutionary algorithm is used to optimize the controller coefficients and identify the friction parameters. Finally, the contrast experiments of four control strategies (the traditional PD control, the PD control with friction feedforward compensation without evolutionary algorithm tuning, the PD control with friction feedforward compensation based on the differential evolution algorithm, and the PD control with friction feedforward compensation based on the genetic algorithm) are carried out on the experimental platform. The experimental results reveal that the evolutionary algorithm-based friction feedforward compensation greatly improves the position tracking accuracy and positioning accuracy, and that the differential evolution-based case achieves better accuracy. Also, the system with the friction feedforward compensation still maintains high accuracy and strong stability in the case of load.

Demonstrating the Potential of Using Transcutaneous Oxygen and Carbon Dioxide Tensions to Assess the Risk of Pressure Injuries

Pressure injuries have a high incidence in elderly and critically ill patients, and can endanger lives in severe cases. The key to reducing the incidence of pressure injuries is to find an objective, noninvasive, automatic and consistent scientific method for assessing pressure injuries. To serve this need, we conducted a clinical study to investigate the potential of using transcutaneous oxygen tension (TcPO2) and transcutaneous carbon dioxide tension (TcPCO2) for assessing pressure injuries. From the results of the study we found that first, the values of TcPO2 and TcPCO2 are sensitive to the change of pressure imposed on the measured region and to the risk status of a pressure injury when a pressure is imposed. Second, the magnitude of change in TcPO2 and TcPCO2 is higher in patients with a high risk of a pressure injury compared with those who have a low risk. Third, TcPO2 and TcPCO2 are both significantly correlated with the Braden score, the widely used score for assessing the risk of a pressure injury. Therefore, TcPO2 and TcPCO2 have a potential to be an effective and convenient scientific tool for assessing the risk of pressure injuries.

Classification of Sputum Sounds Using Artificial Neural Network and Wavelet Transform

Sputum sounds are biological signals used to evaluate the condition of sputum deposition in a respiratory system. To improve the efficiency of intensive care unit (ICU) staff and achieve timely clearance of secretion in patients with mechanical ventilation, we propose a method consisting of feature extraction of sputum sound signals using the wavelet transform and classification of sputum existence using artificial neural network (ANN). Sputum sound signals were decomposed into the frequency subbands using the wavelet transform. A set of features was extracted from the subbands to represent the distribution of wavelet coefficients. An ANN system, trained using the Back Propagation (BP) algorithm, was implemented to recognize the existence of sputum sounds. The maximum precision rate of automatic recognition in texture of signals was as high as 84.53%. This study can be referred to as the optimization of performance and design in the automatic technology for sputum detection using sputum sound signals.

Pneumatic Rotary Actuator Position Servo System Based on ADE-PD Control

In order to accurately control the rotation position of a pneumatic rotary actuator, the flow state of the gas and the motion state of the pneumatic rotary actuator in the pneumatic rotary actuator position servo system are analyzed in this paper. The mathematical model of the system and the experiment platform are established after that. An Adaptive Differential Evolution (ADE) algorithm which adaptively ameliorates the scaling factor and crossover probability in the process of individual evolution is proposed and applied to the parameter optimization of PD controller. The experimental platform is used to compare the controller with Differential Evolution (DE) algorithm and NCD-PID controller. Finally, the characteristics of the system are tested by increasing the inertial load. The experimental results illustrate that system using ADE-PD control strategy has greater position precision and faster response than using DE-PD and NCD-PID strategies, and shows great robustness.

Dimensionless Energy Conversion Characteristics of an Air-Powered Hydraulic Vehicle

Due to the advantages of resource conservation and less exhaust emissions, compressed air-powered vehicle has attracted more and more attention. To improve the power and efficiency of air-powered vehicle, an air-powered hydraulic vehicle was proposed. As the main part of the air-powered hydraulic vehicles, HP transformer (short for Hydropneumatic transformer) is used to convert the pneumatic power to higher hydraulic power. In this study, to illustrate the energy conversion characteristics of air-powered hydraulic vehicle, dimensionless mathematical model of the vehicle’s working process was set up. Through experimental study on the vehicle, the dimensionless model was verified. Through simulation study on the vehicle, the following can be obtained: firstly, the increase of the hydraulic chamber orifice and the area ratio of the pistons can lead to a higher output power, while output pressure is just the opposite. Moreover, the increase of the output pressure and the aperture of the hydraulic chamber can lead to a higher efficiency, while area ratio of the pistons played the opposite role. This research can be referred to in the performance and design optimization of the HP transformers.