BACKGROUND: In clinic,the mechanical study about fibula reconstruction for the repair of mandibular bone defect is unrealistic; the finite element analysis, however, provides a new approach for the biomechanical study of mandibular reconstruction. OBJECTIVE: To establish the three-dimensional finite element model of mandibular body defect under fibula reconstruction and smal titanium plate fixation, and to analyze the biomechanical features. METHODS:The three-dimensional model of mandibular body defect under fibula reconstruction and internal fixation was established. 100 N bite force was loaded on the anterior teeth, contralateral first molar and contralateral second molar, respectively. The maximum stress and maximum displacement before and after model reconstruction, the stress of bone tissues around the titanium plate and titanium screw holes under anterior and posterior loading, and the maximum displacement of the front and rear ends of the fibula under anterior and posterior loading were observed. RESULTS AND CONCLUSION:The maximum stress of the normal mandible concentrated in the condylar neck. In the reconstructed models, the maximum stress concentrated in the contralateral condylar neck. Under the same bite force, the maximum stress value of the reconstructed mandibular model was greater than that of the normal mandible. The maximum stress value of the anterior teeth was greater than that of the posterior teeth. The stress value was maximal between two screw holes inside each titanium plate and almost concentrated in the mandibular angle. The maximum stress of the residual titanium screw of the mandible concentrated in the first titanium screw over the mandibular defect under loading, while the maximum stress of the titanium screw of the fibular end concentrated in the titanium screw below the mesial segment of the fibula. The cortical bone around the screw holes located at the residual end of the mandible near the defect area and the upper plate of the mesial segment of the fibula was the maximum stress concentrated site, and the maximum stress of anterior tooth loading was greater than that of the posterior tooth loading. The displacement values of the fibula gradualy reduced from the upper edge to the lower edge in the X-axis, from the anterior and posterior ends to the middle part in the Y-axis, as wel as from the anterior end to the posterior end in the Z-axis. The maximum displacement values of the anterior and posterior ends of the fibula were at the Z-axis and Y-axis, respectively. The maximum displacement value under anterior tooth loading was greater than that under posterior tooth loading. These results show that the titanium plate over the mandibular angle that is most easy to break should be reinforced. If the stress of titanium screw tip and neck is relatively large, double cortical titanium screw is preferred; if the stress of titanium screw and titanium plate at the fibula end and residual end of the mandible is relatively large, we should pay attention to their stability and fixation; if the stress of anterior tooth occlusion is greater than that of posterior tooth occlusion, anterior tooth occlusion should be avoided after repair.

This paper presents a method to abstract high f requency components from ECG.A new signal averaging method based on vectorcardio graphic loop matched alignment is proposed. It improves the crucial estimation o f signal averaging and ensures that every one of the cardiographic signals parti cipating in signal averaging comes from the same heart beat, so that each of thr ee leads at least has uniform low pass filter effect.These conclusions have been confirmed by the analysis of ECG in clinical test.

The principle of human respiratory function test is decleared. The innovative testing parameters is proposed to optimize traditional calculation parameters based on a respiratory function test of one-time max respiratory flow and pressure. The parameters of respiratory function evaluation was preliminarily verified, and we have already got the expected experimental result. The research can be a valuable reference for the following respiratory function test in future.
Algorithms ; Humans ; Respiratory Function Tests

A wireless wearable sleep monitoring system based on EEG signals is developed.The collected EEG signals are wirelessly sent to the PC or mobile phone Bluetooth APP for real-time display.The system is small in size,low in power consumption,and light in weight.It can be worn on the patient's forehead and is comfortable.It can be applied to home sleep monitoring scenarios and has good application value.The key performance indicators of the system are compared with the industry-related medical device measurement standards,and the measurement results are better than the special standards.

Pulse rate and blood oxygen levels are crucial physiological parameters that reflect physiological and pathological information within the human body.The system designs a wireless pulse wave monitoring system utilizing a flexible reflective probe and the AFE4490,which is capable of monitoring pulse wave and blood oxygen levels on the human forehead.The system is predominantly based on a reflective flexible probe,the AFE4490,a power supply module,a control microcontroller unit(MCU),and a Wi-Fi module.Post-processing by a slave computer,the collected pulse wave data is wirelessly transmitted to a smartphone.The real-time pulse waveform,pulse rate,and blood oxygen levels are displayed on an application.Following relevant tests and verifications,the system can accurately detect pulse wave signals,meet the requirements for wearable technology,and possesses significant market application potential.

Fetal ECG monitoring is a routine clinical detection method that can reflect the changes of fetal heart in utero in real time. At present, most of the clinical fetal heart rate detection adopts the ultrasonic Doppler method, which is technically difficult and highly specialized in operation and expensive. This study introduces a fetal ECG detection system based on the maternal abdominal electrode method. The weak fetal ECG changes are sensed through the maternal abdominal electrode, and the mixed ECG signal is obtained through the corresponding amplification and filtering circuit. Finally, the obtained signal is passed through WiFi, transmitted to the host computer. The host computer uses the adaptive filtering algorithm to estimate the fetal ECG signal. The system has strong feasibility, low operation expertise, low cost, and is more convenient.

In order to solve the problem of wide input range of photocurrent, aiming at the shortage of existing pulse signal acquisition system, an adaptive pulse signal acquisition system based on ADS125H02 is designed, which has high collection accuracy, low noise, anti-interference, wide input range, high integration, etc. The measurement range of the system can reach ±10 V, and the accuracy is 0.009 μV. Experimental tests show that the design of the system can extract weak pulse signals, and has good practicality.
Heart Rate

Body temperature is an essential physiological parameter. Conducting non-contact, fast and accurate measurement of temperature is increasing important under the background of COVID-19. The study introduces an infrared temperature measurement system based on the thermopile infrared temperature sensor ZTP-135SR. Extracting original temperature date of sensor, post-amplification and filter processing have been performed to ensure accuracy of the system. In addition, the temperature data of environmental compensation which obtained by polynomial fitting is added to the system to further improve measurement accuracy.
Algorithms ; Body Temperature ; COVID-19 ; Humans ; Temperature ; Thermometers

Body temperature is an important physiological parameter of the human body and is used in medicine to reflect the physiological state and health status of the human body. At present, the commonly used clinical thermometers on the market are mainly divided into contact and non-contact types. Most of them are used for rapid body temperature measurement, and it is not easy to monitor body temperature changes in real time. This article introduces a new wearable wireless body temperature monitoring system based on NTC, which senses through NTC. The temperature changes are amplified and filtered, zeroed, and calibrated, and then the temperature data is uploaded to the mobile phone APP via Bluetooth in real time to achieve real-time accurate measurement of body temperature.
Body Temperature ; Cell Phone ; Humans ; Monitoring, Physiologic ; Temperature ; Wearable Electronic Devices ; Wireless Technology

Atrial fibrillation is a common arrhythmia, and its diagnosis is interfered by many factors. In order to achieve applicability in diagnosis and improve the level of automatic analysis of atrial fibrillation to the level of experts, the automatic detection of atrial fibrillation is very important. This study proposes an automatic detection algorithm for atrial fibrillation based on BP neural network (back propagation network) and support vector machine (SVM). The electrocardiogram (ECG) segments in the MIT-BIH atrial fibrillation database are divided into 10, 32, 64, and 128 heartbeats, respectively, and the Lorentz value, Shannon entropy, K-S test value and exponential moving average value are calculated. These four characteristic parameters are used as the input of SVM and BP neural network for classification and testing, and the label given by experts in the MIT-BIH atrial fibrillation database is used as the reference output. Among them, the use of atrial fibrillation in the MIT-BIH database, the first 18 cases of data are used as the training set, and the last 7 cases of data are used as the test set. The results show that the accuracy rate of 92% is obtained in the classification of 10 heartbeats, and the accuracy rate of 98% is obtained in the latter three categories. The sensitivity and specificity are both above 97.7%, which has certain applicability. Further validation and improvement in clinical ECG data will be done in next study.
Humans ; Atrial Fibrillation/diagnosis* ; Support Vector Machine ; Heart Rate ; Algorithms ; Neural Networks, Computer ; Electrocardiography