Adolescent ; Adult ; Ankle Injuries ; Ankle Joint ; diagnostic imaging ; Female ; Humans ; Ligaments, Articular ; diagnostic imaging ; injuries ; Male ; Middle Aged ; Radiography ; Rupture

The geometric bone model of patients is an important basis for individualized biomechanical modeling and analysis, formulation of surgical planning, design of surgical guide plate, and customization of artificial joint. In this study, a rapid three-dimensional (3D) reconstruction method based on statistical shape model was proposed for femur. Combined with the patient plain X-ray film data, rapid 3D modeling of individualized patient femur geometry was realized. The average error of 3D reconstruction was 1.597-1.842 mm, and the root mean square error was 1.453-2.341 mm. The average errors of femoral head diameter, cervical shaft angle, offset distance and anteversion angle of the reconstructed model were 0.597 mm, 1.163°, 1.389 mm and 1.354°, respectively. Compared with traditional modeling methods, the new method could achieve rapid 3D reconstruction of femur more accurately in a shorter time. This paper provides a new technology for rapid 3D modeling of bone geometry, which is helpful to promote rapid biomechanical analysis for patients, and provides a new idea for the selection of orthopedic implants and the rapid research and development of customized implants.
Humans ; Imaging, Three-Dimensional/methods* ; Tomography, X-Ray Computed/methods* ; Femur/surgery* ; Femur Head ; Lower Extremity

OBJECTIVE: To investigate the feasibility of MRI three-dimensional (3D) reconstruction model in quantifying glenoid bone defect by comparing with CT 3D reconstruction model measurement. METHODS: Forty patients with shoulder anterior dislocation who met the selection criteria between December 2021 and December 2022 were admitted as study participants. There were 34 males and 6 females with an average age of 24.8 years (range, 19-32 years). The injury caused by sports injury in 29 cases and collision injury in 6 cases, and 5 cases had no obvious inducement. The time from injury to admission ranged from 4 to 72 months (mean, 28.5 months). CT and MRI were performed on the patients' shoulder joints, and a semi-automatic segmentation of the images was done with 3D slicer software to construct a glenoid model. The length of the glenoid bone defect was measured on the models by 2 physicians. The intra-group correlation coefficient ( ICC) was used to evaluate the consistency between the 2 physicians, and Bland-Altman plots were constructed to evaluate the consistency between the 2 methods. RESULTS: The length of the glenoid bone defects measured on MRI 3D reconstruction model was (3.83±1.36) mm/4.00 (0.58, 6.13) mm for physician 1 and (3.91±1.20) mm/3.86 (1.39, 5.96) mm for physician 2. The length of the glenoid bone defects measured on CT 3D reconstruction model was (3.81±1.38) mm/3.80 (0.60, 6.02) mm for physician 1 and (3.99±1.19) mm/4.00 (1.68, 6.38) mm for physician 2. ICC and Bland-Altman plot analysis showed good consistency. The ICC between the 2 physicians based on MRI and CT 3D reconstruction model measurements were 0.73 [95% CI (0.54, 0.85)] and 0.80 [95% CI (0.65, 0.89)], respectively. The 95% CI of the difference between the two measurements of physicians 1 and 2 were (-0.46, 0.49) and (-0.68, 0.53), respectively. CONCLUSION The measurement of glenoid bone defect based on MRI 3D reconstruction model is consistent with that based on CT 3D reconstruction model. MRI can be used instead of CT to measure glenoid bone defects in clinic, and the soft tissue of shoulder joint can be observed comprehensively while reducing radiation.
Male ; Female ; Humans ; Young Adult ; Adult ; Imaging, Three-Dimensional/methods* ; Tomography, X-Ray Computed/methods* ; Joint Instability ; Shoulder Joint/diagnostic imaging* ; Shoulder Dislocation ; Magnetic Resonance Imaging/methods*

The setting and adjustment of ventilator parameters need to rely on a large amount of clinical data and rich experience. This paper explored the problem of difficult decision-making of ventilator parameters due to the time-varying and sudden changes of clinical patient's state, and proposed an expert knowledge-based strategies for ventilator parameter setting and stepless adaptive adjustment based on fuzzy control rule and neural network. Based on the method and the real-time physiological state of clinical patients, we generated a mechanical ventilation decision-making solution set with continuity and smoothness, and automatically provided explicit parameter adjustment suggestions to medical personnel. This method can solve the problems of low control precision and poor dynamic quality of the ventilator's stepwise adjustment, handle multi-input control decision problems more rationally, and improve ventilation comfort for patients.
Humans ; Ventilators, Mechanical ; Respiration, Artificial ; Neural Networks, Computer

When performing eye movement pattern classification for different tasks, support vector machines are greatly affected by parameters. To address this problem, we propose an algorithm based on the improved whale algorithm to optimize support vector machines to enhance the performance of eye movement data classification. According to the characteristics of eye movement data, this study first extracts 57 features related to fixation and saccade, then uses the ReliefF algorithm for feature selection. To address the problems of low convergence accuracy and easy falling into local minima of the whale algorithm, we introduce inertia weights to balance local search and global search to accelerate the convergence speed of the algorithm and also use the differential variation strategy to increase individual diversity to jump out of local optimum. In this paper, experiments are conducted on eight test functions, and the results show that the improved whale algorithm has the best convergence accuracy and convergence speed. Finally, this paper applies the optimized support vector machine model of the improved whale algorithm to the task of classifying eye movement data in autism, and the experimental results on the public dataset show that the accuracy of the eye movement data classification of this paper is greatly improved compared with that of the traditional support vector machine method. Compared with the standard whale algorithm and other optimization algorithms, the optimized model proposed in this paper has higher recognition accuracy and provides a new idea and method for eye movement pattern recognition. In the future, eye movement data can be obtained by combining it with eye trackers to assist in medical diagnosis.
Animals ; Support Vector Machine ; Whales ; Eye Movements ; Algorithms

Motor imagery electroencephalogram (EEG) signals are non-stationary time series with a low signal-to-noise ratio. Therefore, the single-channel EEG analysis method is difficult to effectively describe the interaction characteristics between multi-channel signals. This paper proposed a deep learning network model based on the multi-channel attention mechanism. First, we performed time-frequency sparse decomposition on the pre-processed data, which enhanced the difference of time-frequency characteristics of EEG signals. Then we used the attention module to map the data in time and space so that the model could make full use of the data characteristics of different channels of EEG signals. Finally, the improved time-convolution network (TCN) was used for feature fusion and classification. The BCI competition IV-2a data set was used to verify the proposed algorithm. The experimental results showed that the proposed algorithm could effectively improve the classification accuracy of motor imagination EEG signals, which achieved an average accuracy of 83.03% for 9 subjects. Compared with the existing methods, the classification accuracy of EEG signals was improved. With the enhanced difference features between different motor imagery EEG data, the proposed method is important for the study of improving classifier performance.
Algorithms ; Brain-Computer Interfaces ; Electroencephalography/methods* ; Humans ; Imagery, Psychotherapy ; Imagination

As a global disease, heart failure affects at least 26 million people, and its prevalence is still rising. Besides, the mortality rate and readmission rate remain high. Advanced heart failure is the terminal stage of various heart diseases, and often requires some treatments other than drug intervention, such as heart transplantation which is the gold standard for treatment of heart failure. However, limited by the number of donors, the number of heart transplants in the world has reached a bottleneck. There is a huge gap between the number of patients who need heart transplants and patients who get hearts for survival successfully in reality. With the exploration and development of mechanical circulation support devices for more than half a century, they have become a wonderful treatment for patients with advanced heart failure. This article will introduce the latest progress of mechanical circulatory support devices at home and abroad from the aspects of temporary and long-term devices.

Attention level evaluation refers to the evaluation of people's attention level through observation or experimental testing, and its research results have great application value in education and teaching, intelligent driving, medical health and other fields. With its objective reliability and security, electroencephalogram signals have become one of the most important technical means to analyze and express attention level. At present, there is little review literature that comprehensively summarize the application of electroencephalogram signals in the field of attention evaluation. To this end, this paper first summarizes the research progress on attention evaluation; then the important methods for electroencephalogram attention evaluation are analyzed, including data preprocessing, feature extraction and selection, attention evaluation methods, etc.; finally, the shortcomings of the current development in the field of electroencephalogram attention evaluation are discussed, and the future development trend is prospected, to provide research references for researchers in related fields.
Humans ; Reproducibility of Results ; Electroencephalography

Objective: To evaluate the effectiveness of hepatitis B vaccination in Fujian province. Methods: Based on the hepatitis B immunization strategy of China, a cohort study was designed, involving the population in Fujian province. The population under study was divided into natural exposure birth cohort before 1992 and the immunization birth cohort after 1992 (including voluntary vaccination cohort and standardized vaccination cohort). By cleaning the database of hepatitis B cases which directly reported through network and looked into the incidence and related death outcomes of acute hepatitis B from 2004 to 2017, the incidence levels of hepatitis B and immunization effects were analyzed and evaluated among different birth cohorts. Results: During the observation period, the overall prevalence of hepatitis B in Fujian province was 44.594 per 100 000, with mortality rate as 0.010 per 100 000. The incidence of natural exposure cohort of birth was 56.885 per 100 000. The incidence of voluntary vaccination cohort of birth was 14.502 per 100 000. Compared with the voluntary vaccination cohort, the risk of hepatitis B increased significantly in the natural exposed cohort (RR=3.923), and the difference was statistically significant (P=0.000 7), with attributable risk as 42.383 per 100 000. The attributable risk ratio was 74.507. The population attributable risk ratio was 70.967%. The population attributable risk was 35.448 per 100 000. The attributable rate in standardized vaccination cohorts born after 2002 was 2.336 per 100 000. Compared with the cohorts born before 1992, the RR was 24.347 (P=0.000 0), the attributable risk was 54.549 per 100 000, and the attributable risk ratio was 95.893%, the population attributable risk ratio was 95.300%, the population attributable risk was 47.371 per 100 000, comparing to the natural exposed population. Conclusions: The effectiveness of hepatitis B immunization program had been remarkable in Fujian province since 1992. However, further studies on the persistency of hepatitis B vaccine immunization and its public health significance still needed to be carried out.
China/epidemiology* ; Cohort Studies ; Hepatitis B/prevention & control* ; Hepatitis B Vaccines/administration & dosage* ; Humans ; Immunization ; Incidence ; Odds Ratio ; Prevalence ; Risk Factors ; Vaccination/statistics & numerical data*

Objective: To explore the association between the consumption of chemical fertilizers and the risk of low birth weight (LBW), to provide references for prevention programs on LBW and to improve the birth outcomes. Methods: Stratified multivariate logistic regression method was used in this study involving 153 preterm LBW infants, 179 term LBW infants and 204 normal control infants that were randomly selected from the birth monitoring data between October 2007 and September 2012 in Pingding county, Shanxi province. Associations between the risk of LBW and maternal exposure to chemical fertilizers during pregnancy were identified. A normal control group was set up to compare results between preterm and term LBW groups. Results: Totally, 18 749 infants were born between 2007 and 2012, with the total incidence rates of LBW as 48.5‰, preterm LBW as 19.4‰, and term LBW as 29.1‰. Concerning the case control study on preterm LBW, after adjustment for confounding factors, the risk of preterm LBW appeared 2.51 (95%CI: 1.05-5.99) times higher in villages with annual consumption of chemical fertilizer ≥100 tons than those villages that using chemical fertilizer less than 50 tons. No significant statistical associations were found between the amounts of household chemical fertilizer consumption and the risks of preterm LBW. Regarding the case control study on term LBW, after adjustment for confounding factors, in villages with ≥100 tons annual consumption of chemical fertilizers, the risk of term LBW was 4.03 (95%CI: 1.63-9.92) times of the risk in villages where the annal use of chemical fertilizers was less than 50 tons. There was no significant association between household consumption of chemical fertilizers and the risk of term LBW. Conclusions: Maternal exposure to chemical fertilizers during pregnancy was associated with the risk of LBW. Our findings suggested that the amount of chemical fertilizer consumption in rural areas seemed also associated with the risks of other adverse pregnancy outcomes. Women should avoid the chance of exposure to chemical fertilizers during pregnancy and the consumption of chemical fertilizers should be carefully managed.
Adult ; Case-Control Studies ; Environmental Exposure/adverse effects* ; Female ; Fertilizers/adverse effects* ; Humans ; Infant ; Infant, Low Birth Weight ; Infant, Newborn ; Maternal Exposure ; Pregnancy ; Premature Birth/epidemiology* ; Random Allocation ; Risk Factors