ObjectiveTo evaluate the clinical therapeutic effect of support plates on Schatzker type Ⅳ tibial plateau fractures.MethodsPatients with Schatzker type Ⅳ tibial plateau fractures underwent support plates treatment between April 2013 and September 2014 by using the medial incision or posterior medial incision, if necessary, with other auxiliary incisions, with limited contact compression plate, 1/3 tubular plate or " T” plate to support the fracture. ResultsA total of 14 patients including 6 males and 8 females with an average age of (35.2±9.8) years (ranged from 20 to 52 years) were enrolled in this study and followed up for 12–25 months with an average of (16.3±4.0) months. The knee joints were flexed 80–130° with an average of (97.9±13.1)° one month after the surgery and 90–140° with an average of (119.3±12.1)° three months after the surgery. One year postoperatively, the mean Hospital of Special Surgery knee score ranged from 78 to 96 with an average of 88.4±4.9. Last follow-up assessment of knee function according to Rasmussen scoring system showed excellent in 8 cases, good in 4 cases, and fair in 2 cases; the excellent and good rate was 85.7%. No postoperative complications such as infection, nonunion, vascular nerve injury, or internal fixation failure occurred. ConclusionThe support plates for the treatment of Schatzker type Ⅳ tibial plateau fractures can maintain good reduction, prevent the secondary collapse of the tibial plateau, ensure that knee joint has good alignment, less complications with vascular or nerve injuries, and finally get a satisfied function recovery.
Open reduction and internal fixation with plate and screw is one of the most widely used surgical methods in the treatment of proximal humeral fractures in the elderly. In recent years, more and more studies have shown that it is very important to strengthen the medial column support of the proximal humerus during the surgery. At present, orthopedists often use bone graft, bone cement, medial support screw and medial support plate to strengthen the support of the medial column of the proximal humerus when applying open reduction and internal fixation with plate and screw to treat proximal humeral fractures. Therefore, the methods of strengthening medial column support for proximal humerus fractures and their effects on maintaining fracture reduction, reducing postoperative complications and improving functional activities of shoulder joints after operation are reviewed in this paper. It aims to provide a certain reference for the individualized selection of medial support methods according to the fracture situation in the treatment of proximal humeral fractures.
The in-vivo electron paramagnetic resonance (EPR) method can be used for on-site, rapid, and non-invasive detection of radiation dose to casualties after nuclear and radiation emergencies. For in-vivo EPR spectrum analysis, manual labeling of peaks and calculation of signal intensity are often used, which have problems such as large workload and interference by subjective factors. In this study, a method for automatic classification and identification of in-vivo EPR spectra was established using support vector machine (SVM) technology, which can in-batch and automatically identify and screen out invalid spectra due to vibration and dental surface water interference during in-vivo EPR measurements. In this study, a spectrum analysis method based on genetic algorithm optimization neural network (GA-BPNN) was established, which can automatically identify the radiation-induced signals in in-vivo EPR spectra and predict the radiation doses received by the injured. The experimental results showed that the SVM and GA-BPNN spectrum processing methods established in this study could effectively accomplish the automatic spectra classification and radiation dose prediction, and could meet the needs of dose assessment in nuclear emergency. This study explored the application of machine learning methods in EPR spectrum processing, improved the intelligence level of EPR spectrum processing, and would help to enhance the efficiency of mass EPR spectra processing.
Aiming at the status of muscle and joint damage caused on surgeons keeping surgical posture for a long time, this paper designs a medical multi-position auxiliary support exoskeleton with multi-joint mechanism by analyzing the surgical postures and conducting conformational studies on different joints respectively. Then by establishing a human-machine static model, this study obtains the joint torque and joint force before and after the human body wears the exoskeleton, and calibrates the strength of the exoskeleton with finite element analysis software. The results show that the maximum stress of the exoskeleton is less than the material strength requirements, the overall deformation is small, and the structural strength of the exoskeleton meets the use requirements. Finally, in this study, subjects were selected to participate in the plantar pressure test and biomechanical simulation with the man-machine static model, and the results were analyzed in terms of plantar pressure, joint torque and joint force, muscle force and overall muscle metabolism to assess the exoskeleton support performance. The results show that the exoskeleton has better support for the whole body and can reduce the musculoskeletal burden. The exoskeleton mechanism in this study better matches the actual working needs of surgeons and provides a new paradigm for the design of medical support exoskeleton mechanism.
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.
ObjectiveTo explore the correlation between quality of life and social support and anxiety level in children with epilepsy. MethodsA total of 207 children with epilepsy and their parents from March 2023 to December 2023 from Shanghai Children's Hospitalwere selected as the investigation objects, and the children's quality of life scale, Children's perceptive Social support Scale and PROMIS parental Report version anxiety brief form were used to investigate. The correlation between the quality of life of children with epilepsy and the level of social support and anxiety was analyzed. ResultsThe results of univariate analysis showed that the quality of life of children with epilepsy was affected by whether they had siblings and the frequency of onset in the past month (P<0.05). Pearson correlation analysis showed that social support was positively correlated with quality of life (P<0.05). The scores of anxiety and quality of life were negatively correlated (P<0.05). Social support was negatively correlated with anxiety scores (P<0.05). The results of multiple linear regression analysis showed that siblings, social support and anxiety were independent factors affecting the quality of life of children with epilepsy (P<0.05). ConclusionSocial support has a positive effect on the quality of life of children with epilepsy, anxiety level has a negative effect on the quality of life, and social support has a negative effect on anxiety. Therefore, clinical psychological support should be strengthened for children with epilepsy, fully mobilize their positive psychological factors, reduce their anxiety and other negative emotions, play a full range of social support, to achieve the goal of improving the quality of life.
Abstract： Objective To assess the effects of three different palliative procedures including modified BlalockTaussig (B-T) shunt, Waterston shunt, and reconstruction of right ventricularpulmonary artery (RV-PA) continuity for pulmonary atresia with ventricular septal defect (PAVSD). Methods We retrospectively analyzed the clinical data of 93 patients with PAVSD who had undergone palliative surgical procedures including modifie BT shunt, Waterston shunt, and RVPA econstruction in Fu Wai Hospital from September 1998 to September 2008. There were 53 males and 40 females, aged from 14.0 days to 14.4 years, with the body weight ranged from 3.6 to 33.0 kg (9.9±6.3 kg). According to International Congenital Heart Surgery Nomenclature and Database Project, these patients were categorized into 2 groups: 64 of type Ⅰ and 29 of type Ⅱ. The most common associated anomaly is rightsided aortic arch (except for ventricular septal defect). The application of the three kinds of palliative surgical procedures in staged management of PAVSD and the followup results were statistically analyzed. Results The corrective rate of the three palliative procedures were 28.12% (18/64) for modified BT shunt, 7.14%(1/14) for Waterston shunt, and 66.67% (10/15) for RV-PA reconstruction, respectively. RV-PA reconstruction had a significantly higher corrective 〖CM(1585mm〗rate than the other two surgical procedures (P=0.016). The percutaneous oxygen saturation (SpO2) increased by 4%59% and Nakata index by 31-104 mm2/m2. No tortuous pulmonary artery was found under echocardiogram or angiocardiography after palliative operation. The perioperative mortality of both surgical stages was 10 patients. Twostage radical surgery was successfully performed for 25 patients, among whom 20 were followed up till May 2009. During the followup, one died suddenly, 15 were classified as New York Heart Association (NYHA) Ⅰ, and 4 as NYHA Ⅱ. Conclusion The surgical management of PAVSD needs to be improved continuously. Compared with shunting procedures, the RVPA reconstruction is a better palliative operation method, and the modified B-T shunt is preferred in younger patients.
In order to improve the motion fluency and coordination of lower extremity exoskeleton robots and wearers, a pace recognition method of exoskeleton wearer is proposed base on inertial sensors. Firstly, the triaxial acceleration and triaxial angular velocity signals at the thigh and calf were collected by inertial sensors. Then the signal segment of 0.5 seconds before the current time was extracted by the time window method. And the Fourier transform coefficients in the frequency domain signal were used as eigenvalues. Then the support vector machine (SVM) and hidden Markov model (HMM) were combined as a classification model, which was trained and tested for pace recognition. Finally, the pace change rule and the human-machine interaction force were combined in this model and the current pace was predicted by the model. The experimental results showed that the pace intention of the lower extremity exoskeleton wearer could be effectively identified by the method proposed in this article. And the recognition rate of the seven pace patterns could reach 92.14%. It provides a new way for the smooth control of the exoskeleton.
ST segment morphology is closely related to cardiovascular disease. It is used not only for characterizing different diseases, but also for predicting the severity of the disease. However, the short duration, low energy, variable morphology and interference from various noises make ST segment morphology classification a difficult task. In this paper, we address the problems of single feature extraction and low classification accuracy of ST segment morphology classification, and use the gradient of ST surface to improve the accuracy of ST segment morphology multi-classification. In this paper, we identify five ST segment morphologies: normal, upward-sloping elevation, arch-back elevation, horizontal depression, and arch-back depression. Firstly, we select an ST segment candidate segment according to the QRS wave group location and medical statistical law. Secondly, we extract ST segment area, mean value, difference with reference baseline, slope, and mean squared error features. In addition, the ST segment is converted into a surface, the gradient features of the ST surface are extracted, and the morphological features are formed into a feature vector. Finally, the support vector machine is used to classify the ST segment, and then the ST segment morphology is multi-classified. The MIT-Beth Israel Hospital Database (MITDB) and the European ST-T database (EDB) were used as data sources to validate the algorithm in this paper, and the results showed that the algorithm in this paper achieved an average recognition rate of 97.79% and 95.60%, respectively, in the process of ST segment recognition. Based on the results of this paper, it is expected that this method can be introduced in the clinical setting in the future to provide morphological guidance for the diagnosis of cardiovascular diseases in the clinic and improve the diagnostic efficiency.
Heart sound signal is a kind of physiological signal with nonlinear and nonstationary features. In order to improve the accuracy and efficiency of the phonocardiogram (PCG) classification, a new method was proposed by means of support vector machine (SVM) in which the complete ensemble empirical modal decomposition with adaptive noise (CEEMDAN) permutation entropy was as the eigenvector of heart sound signal. Firstly, the PCG was decomposed by CEEMDAN into a number of intrinsic mode functions (IMFs) from high to low frequency. Secondly, the IMFs were sifted according to the correlation coefficient, energy factor and signal-to-noise ratio. Then the instantaneous frequency was extracted by Hilbert transform, and its permutation entropy was constituted into eigenvector. Finally, the accuracy of the method was verified by using a hundred PCG samples selected from the 2016 PhysioNet/CinC Challenge. The results showed that the accuracy rate of the proposed method could reach up to 87%. In comparison with the traditional EMD and EEMD permutation entropy methods, the accuracy rate was increased by 18%–24%, which demonstrates the efficiency of the proposed method.
