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In recent years, precise high flow oxygen therapy as a new type of oxygen therapy machine has gradually attracted people’s attention and has been widely used in hospital emergency and clinical treatment of respiratory diseases; especially in recent years, severe coronavirus disease (COVID-19) has played an important role in the treatment of patients. This paper presents a new type of precise high flow oxygen therapy machine with electromagnetic pneumatic flow valve as the core control element. A sliding mode control strategy based on the system is proposed to realize the accurate control of oxygen concentration and output flow of oxygen therapy mixture. The physical equipment of the precision high flow system is established, and its working performance is verified through the test platform. The optimization design goal of the precision high flow equipment is achieved.

Spinal cord injury (SCI) is an existing incurable disease that brings great pain and life obstacles to patients. Spinal cord electrical stimulation is an effective means to alleviate spinal cord injury. However, its complicated mechanism of action is still unclear. This article aims to summarize several different spinal cord electrical stimulation methods, analyze the stimulation effect, and briefly describe the current understanding of its origin and mechanism of action. In recent years, several application cases of the electrical stimulation system of stimulation methods have confirmed its positive effects in spinal cord injury diseases and provided new perspectives for the improvement of spinal cord injury. Finally, the possible development direction and corresponding challenges of spinal cord electrical stimulation in the future are proposed.

Cough is a respiratory protective behavior for clearing the secretion. The cough process can be characterized by three features which are cough peak flow rate, peak velocity time, and cough expired volume. The cough expired volume (CEV) and the cough peak flow rate (CPFR) are important for medical diagnosis and cough effectiveness assessment. In this study, the CEV and CPFR values of 700 healthy participants were measured and collected by using a portable pulmonary function device. The gender, age, height, weight, and smoking status information of the 700 participants were also collected. Meanwhile, the integration of backpropagation neural network and genetic algorithm (GA-BP) method was developed to estimate CEV and CPFR values. The results showed that the estimation accuracy of GA-BP method exceeds 90%, which indicates that the GA-BP method could be effectively used for CEV and CPFR value estimation. Furthermore, the method proposed in this paper could be useful for medical diagnosis and medical device development.

Power efficiency of two-stroke spark-ignition engine is generally low because improper amount of fuel injection leads to a lot of unburned fuel loss during the engine working process. However, parameters of the fuel injection system are hard to confirm by aviation experiments due to expensive test costs. This paper proposes a method of calibrating injection parameters of two-stroke spark-ignition engine based on thermodynamic simulation and parameter optimum algorithm. Firstly, the one-dimensional thermodynamic model is built according to the internal structure and thermodynamic process of the engine; then, the model parameters are corrected according to the operating principle of the injector; after experimental verification of the model, considering both the engine power sufficiency and fuel economy, Analytic Hierarchy Process method is applied to look for the optimal injection amount and fuel injection advance angle at different engine working speeds; finally, an aeroengine experiment station with an electronic fuel injector system is built. Through simulation and experiment studies, it can be seen that when the engine speed changes from 3000 to 3500 RPM, the oil consumption rate of the optimal results is higher than that of the previous ones; when the aeroengine speed is higher than 4000 RPM, the oil consumption rate results of the optimal method are 10% to 27% higher than the original results. This paper can be a reference in the optimization of UAV aircraft engine.

The synchrony of patient-ventilator interaction affects the process of mechanical ventilation which is clinically applied for respiratory support. The occurrence of patient-ventilator asynchrony (PVA) not only increases the risk of ventilator complications but also affects the comfort of patients. To solve the problem of uncertain patient-ventilator interaction in the mechanical ventilation system, a novel method to evaluate patient-ventilator synchrony is proposed in this article. Firstly, a pneumatic model is established to simulate the mechanical ventilation system, which is verified to be accurate by the experiments. Then, the PVA phenomena are classified and detected based on the analysis of the ventilator waveforms. On this basis, a novel synchrony index SIhao is established to evaluate the patient-ventilator synchrony. It not only solves the defects of previous evaluation indexes but also can be used as the response parameter in the future research of ventilator control algorithms. The accurate evaluation of patient-ventilator synchrony can be applied to the adjustment of clinical strategies and the pathological analyses of patients. This research can also reduce the burden on clinicians and help to realize the adaptive control of the mechanical ventilation and weaning process in the future.