Brain computer interface is a control system between brain and outside devices by transforming electroencephalogram (EEG) signal. The brain computer interface system does not depend on the normal output pathways, such as peripheral nerve and muscle tissue, so it can provide a new way of the communication control for paralysis or nerve muscle damaged disabled persons. Steady state visual evoked potential (SSVEP) is one of non-invasive EEG signals, and it has been widely used in research in recent years. SSVEP is a kind of rhythmic brain activity simulated by continuous visual stimuli. SSVEP frequency is composed of a fixed visual stimulation frequency and its harmonic frequencies. The two-dimensional ensemble empirical mode decomposition (2D-EEMD) is an improved algorithm of the classical empirical mode decomposition (EMD) algorithm which extended the decomposition to two-dimensional direction. 2D-EEMD has been widely used in ocean hurricane, nuclear magnetic resonance imaging (MRI), Lena image and other related image processing fields. The present study shown in this paper initiatively applies 2D-EEMD to SSVEP. The decomposition, the 2-D picture of intrinsic mode function (IMF), can show the SSVEP frequency clearly. The SSVEP IMFs which had filtered noise and artifacts were mapped into the head picture to reflect the time changing trend of brain responding visual stimuli, and to reflect responding intension based on different brain regions. The results showed that the occipital region had the strongest response. Finally, this study used short-time Fourier transform (STFT) to detect SSVEP frequency of the 2D-EEMD reconstructed signal, and the accuracy rate increased by 16%.
Superficial cartilage defect is an important factor that causes osteoarthritis. Therefore, it is very important to investigate the influence of superficial cartilage defects on its surface morphology and mechanical properties. In this study, the knee joint cartilage samples of adult pig were prepared, which were treated by enzymolysis with chymotrypsin and physical removal with electric friction pen, respectively. Normal cartilage and surface treated cartilage were divided into five groups: control group (normal cartilage group), chymotrypsin immersion group, chymotrypsin wiping group, removal 10% group with electric friction pen, and removal 20% group with electric friction pen. The surface morphology and structure of five groups of samples were characterized by laser spectrum confocal microscopy and environmental field scanning electron microscopy, and the mechanical properties of each group of samples were evaluated by tensile tests. The results show that the surface arithmetic mean height and fracture strength of the control group were the smallest, and the fracture strain was the largest. The surface arithmetic mean height and fracture strength of the removal 20% group with electric friction pen were the largest, and the fracture strain was the smallest. The surface arithmetic mean height, fracture strength and fracture strain values of the other three groups were all between the above two groups, but the surface arithmetic mean height and fracture strength of the removal 10% group with electric friction pen, the chymotrypsin wiping group and the chymotrypsin soaking group decreased successively, and the fracture strain increased successively. In addition, we carried out a study on the elastic modulus of different groups, and the results showed that the elastic modulus of the control group was the smallest, and the elastic modulus of the removal 20% group with electric friction pen was the largest. The above study revealed that the defect of the superficial area of cartilage changed its surface morphology and structure, and reduced its mechanical properties. The research results are of great significance for the prevention and repair of cartilage injury.
Lower limb ankle exoskeletons have been used to improve walking efficiency and assist the elderly and patients with motor dysfunction in daily activities or rehabilitation training, while the assistance patterns may influence the wearer’s lower limb muscle activities and coordination patterns. In this paper, we aim to evaluate the effects of different ankle exoskeleton assistance patterns on wearer’s lower limb muscle activities and coordination patterns. A tethered ankle exoskeleton with nine assistance patterns that combined with differenet actuation timing values and torque magnitude levels was used to assist human walking. Lower limb muscle surface electromyography signals were collected from 7 participants walking on a treadmill at a speed of 1.25 m/s. Results showed that the soleus muscle activities were significantly reduced during assisted walking. In one assistance pattern with peak time in 49% of stride and peak torque at 0.7 N·m/kg, the soleus muscle activity was decreased by (38.5 ± 10.8)%. Compared with actuation timing, the assistance torque magnitude had a more significant influence on soleus muscle activity. In all assistance patterns, the eight lower limb muscle activities could be decomposed to five basic muscle synergies. The muscle synergies changed little under assistance with appropriate actuation timing and torque magnitude. Besides, co-contraction indexs of soleus and tibialis anterior, rectus femoris and semitendinosus under exoskeleton assistance were higher than normal walking. Our results are expected to help to understand how healthy wearers adjust their neuromuscular control mechanisms to adapt to different exoskeleton assistance patterns, and provide reference to select appropriate assistance to improve walking efficiency.
Objective
To analyze the incidence of valve prosthesis-patient mismatch (PPM) and ventricular remodeling of elderly patients after aortic valve replacement (AVR).
Methods
We retrospectively analyzed the clinical data of 134 patient aged over 65 years who underwent AVR for the aortic stenosis or regurgitation at our hospital between January 2016 and December 2016. There were 73 males and 61 females aged 69.7±3.6 years ranging from 65-79 years. The clinical and ultrasound cardiography data were evaluated. PPM was defined as an effective orifice area index (EOAI) of ≤0.85 cm2/m2. The incidence of PPM and the left ventricular remodeling after surgical AVR in the patients with aortic stenosis and aortic regurgitation was analyzed, and the outcomes of aortic valve mechanical prosthesis and aortic valve bioprosthesis were compared.
Results
The incidence of PPM was 32.5% in aortic stenosis and 13.0% in aortic regurgitation (P<0.05). One patient died in the early post-operation, and the incidence of severe PPM was 6.0%.
Conclusion
The incidence of PPM after AVR in the patients with aortic regurgitation is less than that in the patients with aortic stenosis.
Multi-modal brain-computer interface and multi-modal brain function imaging are developing trends for the present and future. Aiming at multi-modal brain-computer interface based on electroencephalogram-near infrared spectroscopy (EEG-NIRS) and in order to simultaneously acquire the brain activity of motor area, an acquisition helmet by NIRS combined with EEG was designed and verified by the experiment. According to the 10-20 system or 10-20 extended system, the diameter and spacing of NIRS probe and EEG electrode, NIRS probes were aligned with C3 and C4 as the reference electrodes, and NIRS probes were placed in the middle position between EEG electrodes to simultaneously measure variations of NIRS and the corresponding variation of EEG in the same functional brain area. The clamp holder and near infrared probe were coupled by tightening a screw. To verify the feasibility and effectiveness of the multi-modal EEG-NIRS helmet, NIRS and EEG signals were collected from six healthy subjects during six mental tasks involving the right hand clenching force and speed motor imagery. These signals may reflect brain activity related to hand clenching force and speed motor imagery in a certain extent. The experiment showed that the EEG-NIRS helmet designed in the paper was feasible and effective. It not only could provide support for the multi-modal motor imagery brain-computer interface based on EEG-NIRS, but also was expected to provide support for multi-modal brain functional imaging based on EEG-NIRS.
In order to conduct surface monitoring of the three-dimensional spine morphology of the human body in daily life, a spine morphology measuring method using "single camera, multi-view" to construct stereo vision is proposed. The images of the back of the human body with landmarks of spinous process are captured from multiple angles by moving a single camera, and based on the "Zhang Zhengyou calibration method" and the triangulation principle of binocular stereo vision, the spatial conversion matrices corresponding to each other between all images and the 3D coordinates of the landmarks are calculated. Then the spine evaluation angle used to evaluate the spine morphology is further calculated. The tests’ results showed that the spine evaluation angle error of this method is within ±3°, and the correlation between the results and the X-ray film Cobb angles is 0.871. The visual detection algorithm used in this paper is non-radioactive, and because only one camera is used in the measurement process and there is no need to pre-set the camera's shooting pose, the operation is simple. The research results of this article can be used in a mobile phone-based intelligent detection system, which will be suitable for the group survey of scoliosis in communities, schools, families and other occasions, as well as for the long-term follow-up of confirmed patients. This will provide a reference for doctors to diagnose the condition, predict the development trend of the condition, and formulate treatment plans.
Aiming at feature selection problem of motor imagery task in brain computer interface (BCI), an algorithm based on mutual information and principal component analysis (PCA) for electroencephalogram (EEG) feature selection is presented. This algorithm introduces the category information, and uses the sum of mutual information matrices between features under different motor imagery category to replace the covariance matrix. The eigenvectors of the sum matrix represent the direction of the principal components and the eigenvalues of the sum matrix are used to determine the dimensionality of principal components. 2005 International BCI competition data set was used in our experiments, and four feature extraction methods were adopted, i. e. power spectrum estimation, continuous wavelet transform, wavelet packet decomposition and Hjorth parameters. The proposed feature selection algorithm was adopted to select and combine the most useful features for classification. The results showed that relative to the PCA algorithm, our algorithm had better performance in dimensionality reduction and in classification accuracy with the assistance of support vector machine classifier under the same dimensionality of principal components.
ObjectiveTo review the research status of anti-infective graft materials and analyze their application prospects, in order to provide inspiration for the development of anti-infective vascular endograft. MethodThe research on endovascular anti-infective grafts at home and abroad was reviewed. ResultsThe anti-infective capability of endovascular graft could be achieved through main approaches like modification of the bulk material, surface modification, or a combination of both. In terms of bulk material modification, this paper delved into the creation of antibacterial composite materials by incorporating other materials into primary materials like metals (such as Mg, Zn), biologically derived materials (such as chitosan, silk fibroin, bacterial cellulose), and synthetic polymers (such as graphene and its derivatives, polyurethane, polylactic acid). Examples included Mg-Nd-Zn-Zr alloy, bacterial cellulose/chitosan nanocrystal composites, and chitosan/silk fibroin composites. For surface modifications, inorganic coatings (such as silver, copper, and nitrides) and organic coatings (such as antibiotics, antimicrobial peptides, and anti-infection polymers) had shown promising antibacterial effects in experiments. ConclusionsThe future research focus is how to synthesize the composite graft material with the mechanical properties of ordinary graft and the cell, blood compatibility and antibacterial properties through nano technology. At the same time, how to synthesize coatings with stable long-term anti-infection and anti-bacterial biofilm performance is also considered to be an important direction of future research.
Objective To investigate the risk factors of high peritoneal transport characteristics in patients with end-stage renal disease undergoing initial continuous ambulatory peritoneal dialysis. Method The clinical data of continuous ambulatory peritoneal dialysis patients who underwent initial peritoneal dialysis and catheterization in the Department of Nephrology, West China Hospital of Sichuan University from January 2011 to December 2017 and completed the peritoneal equilibration test were collected retrospectively. According to the ratio of dialysate to plasma ratio for creatinine at 4 hour [D/Pcr (4h)] in the standard peritoneal equilibration test, the patients were divided into 4 groups (low transport, low average transport, high average transport and high transport). Spearman correlation analysis was used to analyze the related factors of D/Pcr (4h). The risk factors of high peritoneal transport characteristics were analyzed by ordered multi classification logistic regression. Results A total of 647 patients were included. The average age of the patients was (45.85±14.03) years, and the average D/Pcr (4h) was 0.67±0.12. Among them, there were 89 cases (13.76%) in the high transport group, 280 cases (43.28%) in the high average transport group, 234 cases (36.17%) in the low average transport group and 44 cases (6.80%) in the low transport group. Diabetic patients with D/Pcr (4h) were higher than those without diabetes mellitus (0.72±0.12 vs. 0.66±0.12; t=?4.005, P<0.001). Correlation analysis showed that age and 24-h urine volume were positively correlated with D/Pcr (4h); serum albumin, triglyceride, potassium, calcium, magnesium, phosphorus, hemoglobin, serum uric acid and creatinine were negatively correlated with D/Pcr (4h); body surface area (BSA), high sensitivity C-reactive protein, ferritin, cholesterol, sodium, intact parathyroid hormone and estimated giomerular filtration rate had no correlation with D/Pcr (4h). Regression analysis showed that serum albumin [odds ratio (OR)=0.842, 95% confidence interval (CI) (0.809, 0.877), P<0.001], serum uric acid [OR=0.996, 95%CI (0.994, 0.998), P<0.001], magnesium [OR=0.389, 95%CI (0.156, 0.965), P=0.042], BSA [OR=3.916, 95%CI (1.121, 13.680), P=0.032] were correlated with the incidence of peritoneal high transport characteristics. Conclusion Low serum albumin, high BSA, low magnesium and low serum uric acid were independent risk factors for high transport characteristics in initial PD patients.
In the research of non-invasive brain-computer interface (BCI), independent component analysis (ICA) has been considered as a promising method of electroencephalogram (EEG) preprocessing and feature enhancement. However, there have been few investigations and implements about online ICA-BCI system up till now. This paper reports the investigation of the ICA-based motor imagery BCI (MIBCI) system, combining the characteristics of unsupervised learning of ICA and event-related desynchronization (ERD) related to motor imagery. We constructed a simple and practical method of ICA spatial filter calculation and discriminate criterion of three-type motor imageries in the study. To validate the online performance of proposed algorithms, an ICA-MIBCI experimental system was fully established based on NeuroScan EEG amplifier and VC++ platform. Four subjects participated in the experiment of MIBCI testing and two of them took part in the online experiment. The average classification accuracies of the three-type motor imageries reached 89.78% and 89.89% in the offline and online testing, respectively. The experimental results showed that the proposed algorithm produced high classification accuracy and required less time consumption, which would have a prospect of cross platform application.
