Objective:To develop an integrated intelligent device of measurement and calibration for cardiopulmonary resuscitator,so as to improve the efficiency and reliability of measurement and calibration of cardiopulmonary resuscitators,and to ensure the safety and effectiveness of rescuing wounded.Methods:This device used modern sensor transmission technique,and adopted a systematically combined design with industrial control measurement and control module.This device could realize simultaneously automatic detection for a series of parameters included depth and frequency of pressure,single breath frequency,moisture volume and so on in the device of measurement and calibration.Results:The measurement and control of the measurement and calibration device of the integrated cardiopulmonary resuscitator are accurate,which average values of pressure depths were respectively(29.8±0.13)mm,(49.3±0.08)mm and(69.89±0.14)when standard values were respectively 30,50,70 mm.The pressure frequencies were respectively(79.30±0.08)times/min,(99.89±0.14)times/min and(119.94±0.24)times/min when standard values were respectively 80,100 and 120 times/min.The moisture volumes were respectively(347.99±2.77)mL,(546.18±1.89)mL and(746.67±2.14)mL when the standard values were respectively 350,550 and 750mL.The above results of this dive are consistent with the results of the standard device,and the errors of depth and frequency of pressure,and moisture volume were respectively±15%,±10%,±20%,which all were within the allowed range.Conclusion:The measurement and calibration device of integrated intelligence of cardiopulmonary resuscitators can complete various detection of related parameters within one pressure cycle of the cardiopulmonary resuscitator.The detection results of the device are highly consistent with those of the standard device,and the detection results are accurate and reliable.

Driven by the rapid development of comprehensive science and technology and collaborative innovation between medicine and engineering,promote the transformation of healthcare modes. High-definition medicine may become a new healthcare mode that interprets the precise implementation of monitoring,prevention,diagnosis,treatment,rehabilitation,health management,and other interventions throughout the life cycle starting from individual birth. On the basis of reviewing the evolution of medical modes,this article introduces the perspective of healthcare engineering,discusses the connotation of high-definition medicine and its impact on medical development,as well as the empowering role of medical equipment and healthcare technology management response.

Driven by the rapid development of comprehensive science and technology and collaborative innovation between medicine and engineering,promote the transformation of healthcare modes. High-definition medicine may become a new healthcare mode that interprets the precise implementation of monitoring,prevention,diagnosis,treatment,rehabilitation,health management,and other interventions throughout the life cycle starting from individual birth. On the basis of reviewing the evolution of medical modes,this article introduces the perspective of healthcare engineering,discusses the connotation of high-definition medicine and its impact on medical development,as well as the empowering role of medical equipment and healthcare technology management response.

Aiming at the dilemma of expensive and difficult maintenance, lack of technical data and insufficient maintenance force for modern medical equipment, an intelligent fault diagnosis expert system of multi-parameter monitor based on fault tree was proposed in this study. Firstly, the fault tree of multi-parameter monitor was established and analyzed qualitatively and quantitatively, then based on the analysis results of fault tree, the expert system knowledge base and inference engine were constructed and the overall framework of the system was determined, finally the intelligent fault diagnosis expert system for multi-parameter monitor was developed by using the page hypertext preprocessor (PHP) language, with an accuracy rate of 80% in fault diagnosis. The results showed that technology fusion on the basis of fault tree and expert system can effectively realize intelligent fault diagnosis of multi-parameter monitors and provide troubleshooting suggestions, which can not only provide experience accumulation for fault diagnosis of multi-parameter monitors, but also provide a new idea and technical support for fault diagnosis of medical equipment.
Expert Systems ; Monitoring, Physiologic

In order to solve the current problems in medical equipment maintenance, this study proposed an intelligent fault diagnosis method for medical equipment based on long short term memory network(LSTM). Firstly, in the case of no circuit drawings and unknown circuit board signal direction, the symptom phenomenon and port electrical signal of 7 different fault categories were collected, and the feature coding, normalization, fusion and screening were preprocessed. Then, the intelligent fault diagnosis model was built based on LSTM, and the fused and screened multi-modal features were used to carry out the fault diagnosis classification and identification experiment. The results were compared with those using port electrical signal, symptom phenomenon and the fusion of the two types. In addition, the fault diagnosis algorithm was compared with BP neural network (BPNN), recurrent neural network (RNN) and convolution neural network (CNN). The results show that based on the fused and screened multi-modal features, the average classification accuracy of LSTM algorithm model reaches 0.970 9, which is higher than that of using port electrical signal alone, symptom phenomenon alone or the fusion of the two types. It also has higher accuracy than BPNN, RNN and CNN, which provides a relatively feasible new idea for intelligent fault diagnosis of similar equipment.
Algorithms ; Electricity ; Memory, Short-Term ; Neural Networks, Computer

This paper explores the relationship between the cardiac volume and time, which is applied to control dynamic heart phantom. We selected 50 patients to collect their cardiac computed tomography angiography (CTA) images, which have 20 points in time series CTA images using retrospective electrocardiograph gating, and measure the volume of four chamber in 20-time points with cardiac function analysis software. Then we grouped patients by gender, age, weight, height, heartbeat, and utilize repeated measurement design to conduct statistical analyses. We proposed structured sparse learning to estimate the mathematic expression of cardiac volume variation. The research indicates that all patients' groups are statistically significant in time factor ( = 0.000); there are interactive effects between time and gender groups in left ventricle ( = 8.597, = 0.006) while no interactive effects in other chambers with the remaining groups; and the different weight groups' volume is statistically significant in right ventricle ( = 9.004, = 0.005) while no statistical significance in other chambers with remaining groups. The accuracy of cardiac volume and time relationship utilizing structured sparse learning is close to the least square method, but the former's expression is more concise and more robust. The number of nonzero basic function of the structured sparse model is just 2.2 percent of that of least square model. Hence, the work provides more the accurate and concise expression of the cardiac for cardiac motion simulation.

Objective:To establish the emergency medical equipment rental center, not only can reduce the repeated purchase for medical equipment, but also can achieve resource sharing, reduce equipment maintenance cost, and improve utilization efficiency.Methods: To establish emergency medical equipment rental center, which adopted lease mode and centralized management mode to use equipment. Department of medical engineering managed this center and this department is responsible to ensure every clinical department can use equipment by lease method.Results: The center has optimized the resource allocation of hospital, obviously reduced equipment input cost, improved utilization rate of medical facility since it were established. This mode provided reliable service for clinical departments.Conclusion: The established rental center of emergency medical equipment has changed the traditional management mode to a new feasible mode which can improve centralized management for medical devices, reduce waste for medical resource and achieve resource sharing.

Objective:To develop a wearable electro-therapeutic apparatus for chronic soft tissue lesion, which used low frequency electric pulse to treatment the shoulder, back and waist of human body.Methods: The fabric electrodes are fixed on specific position of the elastic vest. The vest elasticity ensures that the electrode and the users are in close contact. MSP430 microcontroller is used as the core of control board. Low frequency pulses for treatment are generated by PWM mode of MSP430 Timer1, then pass through the power amplifier and are added to human body by fabric electrodes. Meanwhile the impedance between electrodes is monitored to avoid the striking fire burns the skin of the human body and ensure user’s safety. The wireless data communication and control between intelligent mobile phone and MSP430 microcontroller are achieved by Bluetooth technology.Results:The developed wearable electrotherapy instrument is easy to operate, safe and reliable, convenient for the daily busy office workers treatment and rehabilitation in working time.Conclusion: It is very fitful for long-term therapy and save the time.

This paper developed an experimental animal cabin with ATM/LP and low oxygen and high carbon dioxide. It is based on the unitized design of modern transmission technology, industrial measurement modules and configuration software. The cabin successfully simulated an enclosed environment of low oxygen and high carbon dioxide at constant pressure, automatically measured and controlled the concentrations of oxygen and carbon dioxide as well as temperature and humidity in the cabin for the first time. The system provided a technology platform for the equipment supporting clinical COPD study. The result is accurate, stable and reliable and can realize automatic measurement and control of cross. The clinical applications show that the cabin with accurate measurement and control is practical and reliable.
Animal Use Alternatives ; instrumentation ; Animals ; Biosensing Techniques ; instrumentation ; Carbon Dioxide ; analysis ; metabolism ; Environment, Controlled ; Equipment Design ; Hypoxia ; Oxygen ; analysis ; Sleep Apnea Syndromes

OBJECTIVETo explore the feasibility of the animal experimental cabin to copy the animal models with ATM/LP and low oxygen and high carbon dioxide environment.

METHODS60 SPF-class male SD rats were divided into two groups, 20 for normobaric hypoxia control experiments and the other 40 for hypobaric hypoxia control experiments. For each group, examine the pulmonary arterial pressure and carotid arterial pressure indicators of rats by using the multi-detector measurement of physiological, and observe the pulmonary vascular changes in the structure.

RESULTSThe ATM/LP and low oxygen and high carbon dioxide environment can promote the formation of pulmonary hypertension and accelerate changes in pulmonary vascular remodeling, promoting right ventricular hypertrophy.

CONCLUSIONClinical applications showed that the animal experimental cabin was observing and controlling accurately, safe, reliable, and the results was reproducible. It can successfully copy the regular low-pressure hypoxia and hypercapnia environment pulmonary hypertension model, in order to study the physiological mechanism of a variety of circulation and respiratory diseases caused by oxygen-poor and provide an experimental technology platform.

Animals ; Carbon Dioxide ; metabolism ; Disease Models, Animal ; Environment, Controlled ; Equipment Design ; Hypoxia ; Male ; Oxygen ; metabolism ; Rats ; Sleep Apnea Syndromes