Automatic sleep staging model based on single channel electroencephalogram signal / 生物医学工程学杂志

Sleep staging is the basis for solving sleep problems. There's an upper limit for the classification accuracy of sleep staging models based on single-channel electroencephalogram (EEG) data and features. To address this problem, this paper proposed an automatic sleep staging model that mixes deep convolutional neural network (DCNN) and bi-directional long short-term memory network (BiLSTM). The model used DCNN to automatically learn the time-frequency domain features of EEG signals, and used BiLSTM to extract the temporal features between the data, fully exploiting the feature information contained in the data to improve the accuracy of automatic sleep staging. At the same time, noise reduction techniques and adaptive synthetic sampling were used to reduce the impact of signal noise and unbalanced data sets on model performance. In this paper, experiments were conducted using the Sleep-European Data Format Database Expanded and the Shanghai Mental Health Center Sleep Database, and achieved an overall accuracy rate of 86.9% and 88.9% respectively. When compared with the basic network model, all the experimental results outperformed the basic network, further demonstrating the validity of this paper's model, which can provide a reference for the construction of a home sleep monitoring system based on single-channel EEG signals.

Single-channel electroencephalogram signal used for sleep state recognition based on one-dimensional width kernel convolutional neural networks and long-short-term memory networks / 生物医学工程学杂志

Aiming at the problem that the unbalanced distribution of data in sleep electroencephalogram(EEG) signals and poor comfort in the process of polysomnography information collection will reduce the model's classification ability, this paper proposed a sleep state recognition method using single-channel EEG signals (WKCNN-LSTM) based on one-dimensional width kernel convolutional neural networks(WKCNN) and long-short-term memory networks (LSTM). Firstly, the wavelet denoising and synthetic minority over-sampling technique-Tomek link (SMOTE-Tomek) algorithm were used to preprocess the original sleep EEG signals. Secondly, one-dimensional sleep EEG signals were used as the input of the model, and WKCNN was used to extract frequency-domain features and suppress high-frequency noise. Then, the LSTM layer was used to learn the time-domain features. Finally, normalized exponential function was used on the full connection layer to realize sleep state. The experimental results showed that the classification accuracy of the one-dimensional WKCNN-LSTM model was 91.80% in this paper, which was better than that of similar studies in recent years, and the model had good generalization ability. This study improved classification accuracy of single-channel sleep EEG signals that can be easily utilized in portable sleep monitoring devices.

Review on identity feature extraction methods based on electroencephalogram signals / 生物医学工程学杂志

Biometrics plays an important role in information society. As a new type of biometrics, electroencephalogram (EEG) signals have special advantages in terms of versatility, durability, and safety. At present, the researches on individual identification approaches based on EEG signals draw lots of attention. Identity feature extraction is an important step to achieve good identification performance. How to combine the characteristics of EEG data to better extract the difference information in EEG signals is a research hotspots in the field of identity identification based on EEG in recent years. This article reviewed the commonly used identity feature extraction methods based on EEG signals, including single-channel features, inter-channel features, deep learning methods and spatial filter-based feature extraction methods, etc. and explained the basic principles application methods and related achievements of various feature extraction methods. Finally, we summarized the current problems and forecast the development trend.

Sleep apnea automatic detection method based on convolutional neural network / 生物医学工程学杂志

Sleep apnea (SA) detection method based on traditional machine learning needs a lot of efforts in feature engineering and classifier design. We constructed a one-dimensional convolutional neural network (CNN) model, which consists in four convolution layers, four pooling layers, two full connection layers and one classification layer. The automatic feature extraction and classification were realized by the structure of the proposed CNN model. The model was verified by the whole night single-channel sleep electrocardiogram (ECG) signals of 70 subjects from the Apnea-ECG dataset. Our results showed that the accuracy of per-segment SA detection was ranged from 80.1% to 88.0%, using the input signals of single-channel ECG signal, RR interval (RRI) sequence, R peak sequence and RRI sequence + R peak sequence respectively. These results indicated that the proposed CNN model was effective and can automatically extract and classify features from the original single-channel ECG signal or its derived signal RRI and R peak sequence. When the input signals were RRI sequence + R peak sequence, the CNN model achieved the best performance. The accuracy, sensitivity and specificity of per-segment SA detection were 88.0%, 85.1% and 89.9%, respectively. And the accuracy of per-recording SA diagnosis was 100%. These findings indicated that the proposed method can effectively improve the accuracy and robustness of SA detection and outperform the methods reported in recent years. The proposed CNN model can be applied to portable screening diagnosis equipment for SA with remote server.

Research on automatic removal of ocular artifacts from single channel electroencephalogram signals based on wavelet transform and ensemble empirical mode decomposition / 生物医学工程学杂志

The brain-computer interface (BCI) systems used in practical applications require as few electroencephalogram (EEG) acquisition channels as possible. However, when it is reduced to one channel, it is difficult to remove the electrooculogram (EOG) artifacts. Therefore, this paper proposed an EOG artifact removal algorithm based on wavelet transform and ensemble empirical mode decomposition. Firstly, the single channel EEG signal is subjected to wavelet transform, and the wavelet components which involve EOG artifact are decomposed by ensemble empirical mode decomposition. Then the predefined autocorrelation coefficient threshold is used to automatically select and remove the intrinsic modal functions which mainly composed of EOG components. And finally the 'clean' EEG signal is reconstructed. The comparative experiments on the simulation data and the real data show that the algorithm proposed in this paper solves the problem of automatic removal of EOG artifacts in single-channel EEG signals. It can effectively remove the EOG artifacts when causes less EEG distortion and has less algorithm complexity at the same time. It helps to promote the BCI technology out of the laboratory and toward commercial application.

Purse-string suture with single channel gastroscopy for the gastric wall perforation during endoscopic submucosal dissection of gastric fundus / 中国内镜杂志

Objective To evaluate the perforation repair method of purse-string suture with single channel after gastroscopy endoscopic submucosal resection (ESD) in treating gastric submucosalal stromal tumor originating from muscularis propria lay of gastric fundus. Methods 15 patients with GIST from gastric fundus muscularis propria were treated with ESD. The diameters of tumors were from 1.5 ～ 3.5 cm. Purse-string suture with single channel gastroscopy was performed for the gastric wall perforation during ESD. Results All patients underwent repair successfully. The procedure time was 10 ～ 15 min. No severe complications occurred. Conclusion Purse-string suture with single channel gastroscopy is a feasible and effective perforation repair method during ESD of gastric fundus.

Clinical effect of oblique supine lithotomy single-access percutaneous nephrolithotomy combined with FURS in treatment of complex kidney stones / 中国内镜杂志

Objective To observe the clinical effect of oblique supine lithotomy position rigid single-access percutaneous nephrolithotomy combined with FURS in treatment of complex urinary tract stones. Methods From May 2013 to January 2016, 40 cases of multiple kidney stones and staghorn calculi patients underwent oblique supine lithotomy position balloon establish standard single renal access, using percutaneous percutaneous combind with FURS, clinical data of patients, including operative time, blood loss, stone stone clearance rate, hospitalstay, incidence of complications and other indicators. Results The patients were successfully implemented Phase I single-access surgery, the median time 52.5 min, stone stone clearance rate of 100%, before and after surgery no difference in the amount of bleeding, no blood transfusion patients, followed up for 3 months to six months, no significant concurrent operation disease. Conclusion Oblique supine lithotomy bit single-access percutaneous percutaneous combined with FURS treatment of complex renal calculi can improve stone clearance rate, increased patient comfort during surgery to avoid damage to the kidneys multi-channel, shorter operative time, treatment obvious.

The clinical application of single channel and double Chinese-made biliary stent in high biliary malig-nant obstructive jaundice / 实用肿瘤学杂志

Objective To discussion the efficacy and safety of single channel and double chinese -made biliary stent in high biliary malignant hilar obstructive jaundice .Methods We reviewed the clinical data of 24 malignant hilar obstructive jaundice patients treated with single channel and double chinese -made biliary stent from October 2012 to December 2013 retrospectively.Of which 9 cases(study group)were used for single channel and double stenttreatment,and 15 cases(control group)were treated by the bilateral channel;We compared the number of intraoperative percutaneous puncture hepatic duct , radiation exposure doses , operation time , drainage effectiveness and complication rates in the two groups .Results The average number of percutaneous puncture hepatic duct in the study group was 1.44 ±0.53 times,which was significantly lower than the control group (3.73 ±0.70 times).The fluoroscopy time and radiation exposure dose of study group was 1152.22 ±335.61 s and 653.22 ±207.02 mGy,which was slightly less than the control group (1236.93 ±463.43 s and 727.00 ±348.52 mGy),the difference was not statistically significant (P=0.638;P=0.572).Liver function was tested after 4 W, the drainage effectiveness of study group and the control group were 88.9%(eight-nineths),86.7%(thirteen-fifteenths),the difference was not statistically significant .One case occurred bile leakage in the study group ,2 pa-tients with hemobilia in control group ,both groups showed no serious complication .Conclusion The single chan-nel and double chinese -made biliary stent to treat high biliary malignant hilar obstructive jaundice is minimally injured and effective ,which can be selectively applied to treat patients with hepatic hilum malignant obstructive jaundice .

The risk factors of residual stones after single channel percutaneous nephrolithotomy / 重庆医学

Objective To investigate the risk factors and countermeasure of residual stones after single‐channel percutaneous nephrolithotomy for higher stone‐free rate and better operation result .Methods All patients who underwent single‐channel percu‐taneous nephrolithotomy in our hospital from June 2011 to December 2013 were retrospected and the cause of residual stones were analyzed .Results There were 42 patients who had residual stones after operation among total 262 patients undergone single‐chan‐nel PCNL .21 patients had residual stones because the stones they burdened were too complex .7 patients were concerned with com‐plications such as intraoperative hemorrhage .The stone fragments scattered into the calices in 7 patients with overlarge stone during fragmentation .The other causes concerned with stone residue included anatomic structural abnormalities of the kidneys(3 patients) , operation itself inherent limitations(3 patients) ,insufficient practice and experience in operation(1 patients) .Conclusion The main causes concerned with residual stones of single‐channel PCNL are complexity of urinary calculi ,bleeding ,scattering of stone frag‐ments and anatomic structural abnormalities of the kidney .

Functional expression of mechanosensitive two-pore domain potassium channel in human bladder carcinoma cells / 동물의과학연구지

Bladder cancer is a common cancer in smoking men and may correlate with mechanosensitive potassium channels because the urinary bladder is a stretch sensing organ. Two-pore K+ channels (K2P), such as TASK3 and TREK1, have recently been shown to play a critical role in both cell apoptosis and tumorigenesis. Of the channels, TREK1 can be activated by many physiological stimuli, including polyunsaturated fatty acids, and intracellular pH, hypoxia, and neurotransmitters. Here we attempted to determine whether TREK1 is functionally expressed in bladder cancer 253J cells. K2P channels, including TREK1, TREK2, TASK1, TASK3, and TWIK1, were quantified in cultured human bladder cancer 253J cells using real time quantitative RT-PCR (qRT-PCR) analysis. Among them, TREK1-like channel was recorded at a single channel level using the patch-clamp technique. The TREKl-like channel, with single-channel conductance of ~90 pS at -80 mV, was recorded in symmetrical 150 mM KCl using an excised inside-out patch configuration. The current-voltage relationships were linear and were insensitive to tetraethylammonium. The channel was activated by membrane stretch, free fatty acids, and intracellular acidosis. These results with electrophysiological properties resemble to those of K2P channel, for instance, TREK1. Therefore, we conclude that TREK1 channel is functionally present in bladder cancer 253J cells.