Temporal lobe epilepsy is the most common type of epilepsy in clinic. In recent years, many studies have found that patients with temporal lobe epilepsy have different degrees of influence in executive function related fields. This influence may not only exist in a certain field of executive function, but may be affected in several fields, and may be related to the origin site of seizures. However, up to now, there is no unified standard for the composition of executive function, and it is widely accepted that the three core components of executive function are working memory, inhibitory control and cognitive flexibility/switching. In addition, the International League Against Epilepsy proposed a new definition in 2010, and epilepsy is a brain network disease. There is a close relationship between brain neural network and cognitive impairment. According to the cognitive field, the brain neural network can be divided into six types: default mode network, salience network, executive control network, dorsal attention network, somatic motor network and visual network. In recent years, there has been increasing evidence that four related internal brain networks are series in a range of cognitive processes. The executive dysfunction of temporal lobe epilepsy may be related to the changes of functional connectivity of neural network, and may be related to the left uncinate fasciculus. This article reviews the research progress related to executive function in temporal lobe epilepsy from working memory, inhibitory control and cognitive flexibility, and discusses the correlation between the changes of temporal lobe epilepsy neural network and executive function research.
Emotion plays an important role in people's cognition and communication. By analyzing electroencephalogram (EEG) signals to identify internal emotions and feedback emotional information in an active or passive way, affective brain-computer interactions can effectively promote human-computer interaction. This paper focuses on emotion recognition using EEG. We systematically evaluate the performance of state-of-the-art feature extraction and classification methods with a public-available dataset for emotion analysis using physiological signals (DEAP). The common random split method will lead to high correlation between training and testing samples. Thus, we use block-wise K fold cross validation. Moreover, we compare the accuracy of emotion recognition with different time window length. The experimental results indicate that 4 s time window is appropriate for sampling. Filter-bank long short-term memory networks (FBLSTM) using differential entropy features as input was proposed. The average accuracy of low and high in valance dimension, arousal dimension and combination of the four in valance-arousal plane is 78.8%, 78.4% and 70.3%, respectively. These results demonstrate the advantage of our emotion recognition model over the current studies in terms of classification accuracy. Our model might provide a novel method for emotion recognition in affective brain-computer interactions.
ObjectiveTo summarize the effectiveness of nitinol memory alloy two foot fixator with autologous cancellous bone grafting in treating old scaphoid fracture and nonunion.MethodsBetween January 2013 and January 2017, 11 patients of old scaphoid fracture and nonunion were treated with nitinol memory alloy two foot fixator and autologous cancellous bone grafting. All patients were male with an average age of 26.1 years (range, 18-42 years). The fractures were caused by sport in 3 cases, falling in 7 cases, and a crashing object in 1 case. The interval between injury and operation was 6-18 months (mean, 8.9 months). Postoperative outcome measures included operation time, fracture healing time, grip strength, range of motion (ROM) of flexion, extension, ulnar deviation, and radial deviation, Mayo score, visual analogue scale (VAS) score, and the Disabilities of the Arm, Shoulder, and Hand (DASH) score.ResultsThe operation time was 35-63 minutes (mean, 48 minutes). All incisions had primary healing with no infection and loosening or breakage of internal fixator. All patients were followed up 12-30 months (mean, 20.7 months). X-ray films showed that fracture healing was achieved in all patients with an average time of 15 weeks (range, 12-25 weeks). All internal fixators were removed after 10-12 months of operation (mean, 11.2 months). At last follow-up, the grip strength, ROMs of flexion, ulnar deviation, and radial deviation were superior to those before operation (P<0.05), no significant difference was found in ROM of extension between pre- and post-operation (t=0.229, P=0.824). There were significant differences in above indexes between affected and normal sides (P<0.05). At last follow-up, the Mayo, VAS, DASH scores were also significantly superior to those before operation (P<0.05).ConclusionFor the old scaphoid fracture and nonunion, Ni-Ti arched shape-memory alloy fixator and autologous cancellous bone grafting can obtain good effectiveness, which is an effective treatment.
Cardiovascular disease is the leading cause of death worldwide, accounting for 48.0% of all deaths in Europe and 34.3% in the United States. Studies have shown that arterial stiffness takes precedence over vascular structural changes and is therefore considered to be an independent predictor of many cardiovascular diseases. At the same time, the characteristics of Korotkoff signal is related to vascular compliance. The purpose of this study is to explore the feasibility of detecting vascular stiffness based on the characteristics of Korotkoff signal. First, the Korotkoff signals of normal and stiff vessels were collected and preprocessed. Then the scattering features of Korotkoff signal were extracted by wavelet scattering network. Next, the long short-term memory (LSTM) network was established as a classification model to classify the normal and stiff vessels according to the scattering features. Finally, the performance of the classification model was evaluated by some parameters, such as accuracy, sensitivity, and specificity. In this study, 97 cases of Korotkoff signal were collected, including 47 cases from normal vessels and 50 cases from stiff vessels, which were divided into training set and test set according to the ratio of 8 : 2. The accuracy, sensitivity and specificity of the final classification model was 86.4%, 92.3% and 77.8%, respectively. At present, non-invasive screening method for vascular stiffness is very limited. The results of this study show that the characteristics of Korotkoff signal are affected by vascular compliance, and it is feasible to use the characteristics of Korotkoff signal to detect vascular stiffness. This study might be providing a new idea for non-invasive detection of vascular stiffness.
The automatic recognition technology of muscle fatigue has widespread application in the field of kinesiology and rehabilitation medicine. In this paper, we used surface electromyography (sEMG) to study the recognition of leg muscle fatigue during circuit resistance training. The purpose of this study was to solve the problem that the sEMG signals have a lot of noise interference and the recognition accuracy of the existing muscle fatigue recognition model is not high enough. First, we proposed an improved wavelet threshold function denoising algorithm to denoise the sEMG signal. Then, we build a muscle fatigue state recognition model based on long short-term memory (LSTM), and used the Holdout method to evaluate the performance of the model. Finally, the denoising effect of the improved wavelet threshold function denoising method proposed in this paper was compared with the denoising effect of the traditional wavelet threshold denoising method. We compared the performance of the proposed muscle fatigue recognition model with that of particle swarm optimization support vector machine (PSO-SVM) and convolutional neural network (CNN). The results showed that the new wavelet threshold function had better denoising performance than hard and soft threshold functions. The accuracy of LSTM network model in identifying muscle fatigue was 4.89% and 2.47% higher than that of PSO-SVM and CNN, respectively. The sEMG signal denoising method and muscle fatigue recognition model proposed in this paper have important implications for monitoring muscle fatigue during rehabilitation training and exercise.
ObjectiveTo compare the biomechanical characteristics of self-made nickel-titanium shape memory alloy stepped plate with calcaneal plate and cannulated compression screws in fixing calcaneal osteotomy.MethodsCalcaneal osteotomy was operated on 6 fresh-frozen lower limbs collected from donors. Then three kinds of fixation materials were applied in random, including the self-made nickel-titanium shape memory alloy stepped plate (group A), calcaneal plate (group B), and cannulated compression screws (group C). Immediately after fixation, axial loading of 20-600 N and 20 N/s in speed was introduced to record the biomechanical data including maximum displacement, elastic displacement, and maximum load. Then fatigue test was performed (5 Hz in frequency and repeat 3 000 times) and the same axial loading was introduced to collect the biomechanical data. Finally, the axial compression stiffness before and after fatigue test were calculated.ResultsThere was no significant difference in the axial compression stiffness between pre- and post-fatigue test in each group (P>0.05). However, the axial compression stiffness was significant higher in group A than that in groups B and C both before and after fatigue test (P<0.05). No significant difference was found between group B and group C (P>0.05).ConclusionSelf-made nickel-titanium shape memory alloy stepped plate is better than calcaneal plate and cannulated compression screws in axial load stiffness after being used to fix calcaneal osteotomy.
As one of the stimulus-response polymeric intelligent materials, shape memory polymers have been widely applied in biomedicine due to their better biocompatibility, higher controllability, stronger deformation restorability and biodegradability compared with shape memory alloys and shape memory ceramics. This review will introduce the structural principles of shape memory polymers and summarize their applications in the treatment of vascular diseases, especially in endovascular therapy. At the same time, the related technical problems and the future of shape memory polymers are prospected. With the continuous development of processing technology and materials, it can be predicted that shape memory polymers will be more widely used in the medical field.