The pace of modern life is accelerating, the pressure of life is gradually increasing, and the long-term accumulation of mental fatigue poses a threat to health. By analyzing physiological signals and parameters, this paper proposes a method that can identify the state of mental fatigue, which helps to maintain a healthy life. The method proposed in this paper is a new recognition method of psychological fatigue state of electrocardiogram signals based on convolutional neural network and long short-term memory. Firstly, the convolution layer of one-dimensional convolutional neural network model is used to extract local features, the key information is extracted through pooling layer, and some redundant data is removed. Then, the extracted features are used as input to the long short-term memory model to further fuse the ECG features. Finally, by integrating the key information through the full connection layer, the accurate recognition of mental fatigue state is successfully realized. The results show that compared with traditional machine learning algorithms, the proposed method significantly improves the accuracy of mental fatigue recognition to 96.3%, which provides a reliable basis for the early warning and evaluation of mental fatigue.
OBJECTIVE: To investigate the hemodynamic changes of the end-to-end anastomosed arteries with nitinol clips. METHODS: Fifteen New Zealand rabbits were divided into anastomosis clip group, suture group and control group randomly. The carotid arteries were resected and end-to-end anastomosis were carried out with nitinol clips in anastomosis clip group and with traditional suture in suture group. The carotid arteries remained undamaged in control group. On the days of 3, 9, 21 and 30 postoperatively, mean blood velocity (Vm), pulsatility index (PI) and resistance index (RI) of anastomosed arteries were determined by Ultrasonography Doppler. RESULTS: On the days of 8 and 9 postoperatively, there were no significant differences of VM, PI and RI between two experimental groups (P gt; 0.05). On the days of 20 and 30 postoperatively, the differences of Vm and RI were significant (Vm: P lt; 0.01, P lt; 0.05: RI: P lt; 0.01, P lt; 0.05). The hemodynamic restoration of the anastomosis clip group was better than that of the suture group. CONCLUSION: The hemodynamics of arteries anastomosed with nitinol clips is better than that with traditional suture. This technique has practical value clinically.
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.
Objective To investigate the changes of cognitive function of epileptic patients after antiepileptic drugs (AEDs) therapy. Methods Twenty eight cases of epileptic patients with new diagnosis and untreatment from March 2015 to February 2016 were collected. According to the seizure type, degree of attack and drug efficacy, patients were divided into three groups and treated with one of three AEDs, including Lamotrigine (LTG), Oxcarbazepine (OXC), and Sodium valproate (VPA). Among them, 11 were LTG group, 12 were OXC group and 5 were VPA group.Then the patients were followed up for 1 year. The clinical memory scale was used to analyze cognitive function of epileptic patients before and after therapy. Results Compared to 30 cases of healthy volunteers, the scores of memory quotient (P<0.01), directed memory (P<0.05), associative learning (P<0.05) and image free recall (P<0.01) of epileptic patients were obviously decreased before AEDs therapy.AEDs therapy reduced or controlled seizures in new diagnostic epileptic patients, and the total effective rate was 85.7%. In the clinical memory scale tests, the scores of memory quotient (P<0.01), directed memory (P<0.05), associative learning (P<0.05), portrait characteristics contact memory (P<0.05) were improved after therapy. The scores of image free recall and meaningless graphics recognition were also improved, but there was no statistical significance. Besides, there was a statistically significant improvement in the score of portrait characteristics contact memory after LTG treatment (P<0.05), and directed memory after VPA treatment (P<0.05). Conclusions Epileptic patients accompanied with cognitive deficits before drug intervention. Through standard AEDs treatment, seizures could be better controlled. The cognitive function of epileptic patients was not declined after short-term（within 1 year） intervention of LTG, OCX or VPA. Moreover some parts of the cognitive domain could be improved.
Objective To investigate the cl inical effect of the acetabular tridimensional memoryalloy-fixation system (ATMFS) in treatment of posterior wall acetabular fractures with posterior dislocation of hip. Methods From January 2004 to February 2006, 15 cases of posterior wall acetabular fracture with posterior dislocation of hip were treated. There were 11males and 4 females, aged 21-68 years old with an average of 43.5 years old. Injury was caused by traffic accident in 8 cases, by fall ing from height in 5 cases and others in 2 cases. The locations were the left hip in 9 cases and the right hip in 6 cases. According to Thompson-Epstein’ fracture classification, there were 6 cases of type II, 5 cases of type III, 2 cases of type IV and 2 cases of type V. Imaging showed the acetabular articular surface displacement of 2-5 mm(mean 3 mm). The time from injury to hospital ization was 6 hours to 2 weeks(mean 1.5 days). Skeletal traction on femoral condyle was given, manual reduction was performed in 12 patients and intra-operative reduction in 3 cases. ATMFS was used after 2-7 days of hospital ization, and 4 cases received autologous free il ium because of bone defect. Results The operative time was 90-390 minutes with an average of 210 minutes. Intraoperative blood loss was 350-2 500 mL with an average of 360 mL. The hospital ization days of the patients ranged from 7 to 21 days(mean 10 days). Epidermal infection occurred and was cured after symptomatic management in 1 case. Other incisions healed by first intention. No deep infections, pulmonary embol ism, deep venous thrombosis and other compl ications occurred. The patients were followed up 1 to 3 years with an average of 1.6 years. Ischemic necrosis of femoral head occurred in 1 case. Heterotopic ossification in grade II occurred in 1 case. The hip function was still good without special treatment. According to Matta’s X-ray fracture reduction assessment, the results were excellent in 7 cases, good in 5 cases, fair in 2 cases, and poor in 1 case, the excellent and good rate was 80%. According to d’Aubigné cl inical efficacy evaluation, the results were excellent in 8 cases, good in 5 cases, fair in 1 case, and poor in 1 case, the excellent and good rate was 86.7% at last followup. Conclusion ATMFS can be used for the treatment of posterior wall acetabular fracture with posterior dislocation of hip, which can improve the anatomy corresponding rate of the femoral head and reduce the incidence of compl ications and restore the function of the hip.
Repeated transcranial magnetic stimulation (rTMS) is one of the commonly used brain stimulation techniques. In order to investigate the effects of rTMS on the excitability of different types of neurons, this study is conducted to investigate the effects of rTMS on the cognitive function of mice and the excitability of hippocampal glutaminergic neurons and gamma-aminobutyric neurons from the perspective of electrophysiology. In this study, mice were randomly divided into glutaminergic control group, glutaminergic magnetic stimulation group, gamma-aminobutyric acid energy control group, and gamma-aminobutyric acid magnetic stimulation group. The four groups of mice were injected with adeno-associated virus to label two types of neurons and were implanted optical fiber. The stimulation groups received 14 days of stimulation and the control groups received 14 days of pseudo-stimulation. The fluorescence intensity of calcium ions in mice was recorded by optical fiber system. Behavioral experiments were conducted to explore the changes of cognitive function in mice. The patch-clamp system was used to detect the changes of neuronal action potential characteristics. The results showed that rTMS significantly improved the cognitive function of mice, increased the amplitude of calcium fluorescence of glutamergic neurons and gamma-aminobutyric neurons in the hippocampus, and enhanced the action potential related indexes of glutamergic neurons and gamma-aminobutyric neurons. The results suggest that rTMS can improve the cognitive ability of mice by enhancing the excitability of hippocampal glutaminergic neurons and gamma-aminobutyric neurons.
Fetal electrocardiogram signal extraction is of great significance for perinatal fetal monitoring. In order to improve the prediction accuracy of fetal electrocardiogram signal, this paper proposes a fetal electrocardiogram signal extraction method (GA-LSTM) based on genetic algorithm (GA) optimization with long and short term memory (LSTM) network. Firstly, according to the characteristics of the mixed electrocardiogram signal of the maternal abdominal wall, the global search ability of the GA is used to optimize the number of hidden layer neurons, learning rate and training times of the LSTM network, and the optimal combination of parameters is calculated to make the network topology and the mother body match the characteristics of the mixed signals of the abdominal wall. Then, the LSTM network model is constructed using the optimal network parameters obtained by the GA, and the nonlinear transformation of the maternal chest electrocardiogram signals to the abdominal wall is estimated by the GA-LSTM network. Finally, using the non-linear transformation obtained from the maternal chest electrocardiogram signal and the GA-LSTM network model, the maternal electrocardiogram signal contained in the abdominal wall signal is estimated, and the estimated maternal electrocardiogram signal is subtracted from the mixed abdominal wall signal to obtain a pure fetal electrocardiogram signal. This article uses clinical electrocardiogram signals from two databases for experimental analysis. The final results show that compared with the traditional normalized minimum mean square error (NLMS), genetic algorithm-support vector machine method (GA-SVM) and LSTM network methods, the method proposed in this paper can extract a clearer fetal electrocardiogram signal, and its accuracy, sensitivity, accuracy and overall probability have been better improved. Therefore, the method could extract relatively pure fetal electrocardiogram signals, which has certain application value for perinatal fetal health monitoring.