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.
【摘要】目的介紹華西醫院支援西部地區衛生工程項目的實踐和成效。方法過去5年間，華西醫院響應國家號召，通過各種幫扶形式，開展了一系列對口支援活動。結果華西醫院利用自身的資源優勢，通過各種幫扶形式，提高基層醫院的醫療救治水平和綜合服務能力，為建立城市支援農村衛生工作的長效機制進行了積極的實踐和探索，取得顯著成效。結論基層衛生事業與人民健康需求和現代醫學進步存在著相當的差距，醫療體制改革對部屬部管醫院的對口支援提出了更高的要求，對口支援的許多細節還需要我們去進一步完善。【Abstract】Objective To introduce the practice and progress of the supportive rural hygiene program of West China Hospital. Methods In the past five years, West China Hospital had made a lot of supportive rural hygiene practice. Results West China Hospital made good use of its own advantages in resources to develop the treatment level and the comprehensive service capability of primary hospital. West China Hospital did a lot of practice to establish the effective system of assistance of city medical care to rural areas, and had already achieved remarkable effects. Conclusionre is a lot of disparity between the basic public health or the requirement of people and the modern medicine progress. Many details for support should be further consummated.
Hypertension is the primary disease that endangers human health. A convenient and accurate blood pressure measurement method can help to prevent the hypertension. This paper proposed a continuous blood pressure measurement method based on facial video signal. Firstly, color distortion filtering and independent component analysis were used to extract the video pulse wave of the region of interest in the facial video signal, and the multi-dimensional feature extraction of the pulse wave was preformed based on the time-frequency domain and physiological principles; Secondly, an integrated feature selection method was designed to extract the universal optimal feature subset; After that, we compared the single person blood pressure measurement models established by Elman neural network based on particle swarm optimization, support vector machine (SVM) and deep belief network; Finally, we used SVM algorithm to build a general blood pressure prediction model, which was compared and evaluated with the real blood pressure value. The experimental results showed that the blood pressure measurement results based on facial video were in good agreement with the standard blood pressure values. Comparing the estimated blood pressure from the video with standard blood pressure value, the mean absolute error (MAE) of systolic blood pressure was 4.9 mm Hg with a standard deviation (STD) of 5.9 mm Hg, and the MAE of diastolic blood pressure was 4.6 mm Hg with a STD of 5.0 mm Hg, which met the AAMI standards. The non-contact blood pressure measurement method based on video stream proposed in this paper can be used for blood pressure measurement.
Objective To determine whether lymph node-targeted chemotherapy with carbon nanoparticles absorbing 5-FU affects expressions of bcl-2, bax and caspase-3 in gastric cancer tissues, metastatic lymph nodes and normal gastric mucosa. Methods Twenty-eight patients with gastric cancer in our department were divided into lymph node-targeted chemotherapy (LNTC) group and control group from October 2005 to August 2006. The patients were treated with carbon nanoparticles absorbing 5-FU before operation in LNTC group and those were operated directly in control group. The gastric cancer tissues, metastatic lymph nodes and normal gastric mucosa were collected after operation. The expressions of bcl-2, bax and caspase-3 in those tissues were determined by immunohistochemical technique. Results In LNTC group, the positive expression rate of bcl-2 in gastric cancer tissues and metastatic lymph nodes was significantly lower than those in control group (28.6% vs . 78.6% , 25.0% vs . 70.0% , P ＜ 0.05), the positive expression rate of bax (85.7% vs . 28.6% , 80.0% vs . 30.0% ) and caspase-3 (57.1% vs . 14.3% , 55.0% vs . 15.0% ) in gastric cancer tissues and metastatic lymph nodes was significantly higher than those in control group ( P ＜ 0.05). The positive expression rate of bcl-2, bax and caspase-3 in normal gastric mucosa was not significantly different between two groups ( P ＞ 0.05). Conclusion The lymph node-targeted chemotherapy with carbon nanoparticles absorbing 5-FU can down-regulate the expression of bcl-2 and up-regulate the expression of bax and caspase-3 in gastric cancer tissues and metastatic lymph nodes, and therefore by affecting the expression levels of these apoptosis molecules may be one of the ways to induce tumor cell apoptosis.
Objective To assess the effectiveness of psychological intervention on post-stoke depression. Methods Such databases as the JBI Database of Systematic Review (1980 to June, 2010), The Cochrane Library (1980 to June, 2010), PubMed (1966 to 2010), CINAHL(1982 to May, 2000), CBM (1978 to 2010), and CNKI (1979 to 2010) were searched to collect randomized controlled trials (RCTs). In accordance with the predefined inclusion and exclusion criteria, the quality of included studies was evaluated, and then meta-analyses were performed by using RevMan 5.0 software. Results A total of 33 RCTs were included. The results of meta-analyses showed: (1) Compared with the control group, the short-term effect of psychological intervention was more effective in decreasing depression score. The subgroup analysis showed that the intervention effects at the time of four weeks, six weeks, eight weeks, and 12 weeks were better than those of the control group. (2) The long-term effect of psychological intervention was more effective in decreasing depression score. The subgroup analyses showed that the intervention effects at the interval of eight weeks, 24 weeks, and 48 weeks were better than those of the control group. (3) The combined or single application of either cognitive-behavioral psychotherapy or supportive psychotherapy was more effective in decreasing depression score than the control group. However, there was no significant difference between the general psychological treatment group and the control group. (4) The subgroup analyses showed that the different qualities of the included studies were more effective than those of the control group. Conclusion Various psychological intervention is effective in decreasing the patient’s depression score, and cognitive-behavioral therapy and supportive psychotherapy, especially, can significantly improve the depression state and promote recovery.
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.
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.
Objective To explore the management practices of projects supported by National Natural Science Foundation in a large general hospital. Methods We carried out an overall analysis on the data of projects supported by National Natural Science Foundation of China from 2011 to 2016 in West China Hospital of Sichuan University. The characteristics of researchers who were granted the foundation were also studied. Results In the recent six years, there were 767 projects granted by the National Natural Science Foundation in the hospital, with an average of 127 projects a year. The Department of Medical Sciences was the top source of approval for the projects (690 items), and its granted projects covered all the categories set by the foundation committee. Most of the researchers who got the fund were between 25 and 40 years of age (501 projects). Researchers in charge of general projects were mainly professors with an age of (43.54±7.28) years old in average. Researchers in charge of Projects for Distinguished Young Scholars were mainly of medium-grade professional titles, and their average age was (32.01±3.05) years old. Moreover, among these young scholars, the age of male researchers [(31.27±2.23) years old] was significantly younger than that of female scholars [(32.90±3.62) years old](P<0.01). Conclusion It is more and more important for National Natural Science Foundation of China to study the accumulation of early research of young scholars and the leading role of the hospital in basic research, personnel training and discipline construction.
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.
Keloids are benign skin tumors resulting from the excessive proliferation of connective tissue in wound skin. Precise prediction of keloid risk in trauma patients and timely early diagnosis are of paramount importance for in-depth keloid management and control of its progression. This study analyzed four keloid datasets in the high-throughput gene expression omnibus (GEO) database, identified diagnostic markers for keloids, and established a nomogram prediction model. Initially, 37 core protein-encoding genes were selected through weighted gene co-expression network analysis (WGCNA), differential expression analysis, and the centrality algorithm of the protein-protein interaction network. Subsequently, two machine learning algorithms including the least absolute shrinkage and selection operator (LASSO) and the support vector machine-recursive feature elimination (SVM-RFE) were used to further screen out four diagnostic markers with the highest predictive power for keloids, which included hepatocyte growth factor (HGF), syndecan-4 (SDC4), ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2), and Rho family guanosine triphophatase 3 (RND3). Potential biological pathways involved were explored through gene set enrichment analysis (GSEA) of single-gene. Finally, univariate and multivariate logistic regression analyses of diagnostic markers were performed, and a nomogram prediction model was constructed. Internal and external validations revealed that the calibration curve of this model closely approximates the ideal curve, the decision curve is superior to other strategies, and the area under the receiver operating characteristic curve is higher than the control model (with optimal cutoff value of 0.588). This indicates that the model possesses high calibration, clinical benefit rate, and predictive power, and is promising to provide effective early means for clinical diagnosis.