OBJECTIVE: To investigate the new surgical pathway of endoscopic frontal sinus surgery for frontal sinus lesions through the upper-agger nasi approach. METHOD: The computed tomography (CT) scans from 32 patients were collected and subjected to three-dimensional reconstruction by Mimics. The distance in sagittal planes from anterior ethmoid artery to midpoint of axilla and to skull base attachment at anterior middle turbinate was measured. The distance in coronal planes between the perpendicular plate of middle turbinate and the orbital lamina was also detected as well as the height of agger nasi. Three-dimensional structures of the frontal sinus and its surrounding cells was reconstructed by Sinuses Trachea I software. We integrated the CT scans and the above data for simulating surgical operation on cadaveric heads. RESULT: (1) Skull base attachment at anterior middle turbinate located at the anterior or posterior of aperture of frontal sinus. (2) The mean distance between anterior ethmoid artery and midpoint of axilla was (22.23 ± 2.78) mm on the left side and (22.30 ± 2.80) mm on right. The mean distance between anterior ethmoid artery and skull base attachment at anterior middle turbinate was (15.31 ± 2.82) mm on left and (15.39 ± 3.53) mm on right. The distance between perpendicular plate of middle turbinate and orbital lamina was (7.61 ± 1.34) mm on left and (7.80 ± 1.40) mm on right side. The height of the agger nasi was (8.33 ± 2.14) mm on left and (8.00 ± 2.57) mm on right. There was no statistical difference in the above data between left and right side (P > 0.05). (3) The visible three-dimensional structure showed that skull base attachment at the anterior middle turbinate was closely adjoined the aperture of frontal sinus, the space between sub-outer side of the attachment and orbital lamina, above the agger nasi cell or the upper area of the agger nasi cell was solely cell structures. CONCLUSION Endoscopic frontal sinus surgery for frontal sinus lesions through the upper-agger nasi approach was practicable to solitary frontal sinus lesions and to solve the complex frontal sinus or frontal recess lesions by flexible operation according to the feature of the lesions.
Axilla ; Bone Plates ; Endoscopy ; Frontal Sinus ; surgery ; Humans ; Nasal Cavity ; Nose ; Paranasal Sinus Neoplasms ; surgery ; Paranasal Sinuses ; Skull Base ; Software ; Tomography, X-Ray Computed ; Trachea ; Turbinates

OBJECTIVE: To investigate the possibility and anatomy landmark of the frontal beak approach of endoscopic frontal sinusotomy to the frontal sinus lesions. METHOD: (1)Twenty cases of frozen cadaveric head underwent spiral computed tomography scans. Then data were transferred into the Mimics image workstation to reorganize CT images in the coronal, sagittal, and axial planes. The anatomic parameters related to surgical approach points were measured, such as the distance between vertical plate of the middle turbinate and lamina papyracea and the thickness of the frontal beak. (2) 3D visual model of the frontal cell and the drainage way of the frontal sinus was produced with the application of Sinuses Trachea I software. (3)The endoscopic frontal sinus surgery were performed on 20 cases of subjects (objects)to find out the anatomy landmarks of the frontal beak approach, measure the parameters such as the distance between middle turbinate and lamina papyracea, and evaluate the potential surgical complications during operation. RESULT: (1)The frontal beak is a white bony arcs located at the attachment point of middle turbinate front inserted to the skull base. Its position was relatively constant, before frontal sinus above. (2)The distance between the middle turbinate vertical plate and lamina papyracea was (7. 61 ± 1. 34) mm. The thickness of the frontal beak in surgical approach was (3. 27 ± 0. 91) mm. (3) 3D visual structure of the frontal sinus and its ventilation pathway: the shape of unilateral frontal sinus looked like the cone, which was transited by the drainage pathway of the frontal sinus. The front part of the frontal sinus ostium is surrounded by the frontal beak. The upper part the frontal beak connected to the floor of the frontal sinus. (4) Frontal beak can be used as an landmark of frontal beak approach in the endoscopic frontal sinus surgery. But the lateral view of frontal sinus still was limited in the operation. CONCLUSION The endoscopic frontal sinus surgery with the approach of the frontal beak is easy to operate and learn. In this area between the double "L", the operation is safe.
Anatomic Landmarks ; Endoscopy ; methods ; Frontal Sinus ; surgery ; Humans ; Skull Base ; Software ; Tomography, Spiral Computed ; Tomography, X-Ray Computed ; Turbinates ; anatomy & histology

In the paper, it is introduced professor's recognition on the pathogenesis and professor's experience in the treatment of the motor impairment of the trunk after stroke. Professorbelieves that the motor impairment of the trunk after stroke is the essential factor affecting the rehabilitation in stroke. The motor impairment of the trunk after stroke results from brain marrow damage and spiritual impairment. Hence, regaining the consciousness and promoting the circulation of the governor vessel are the basic principles of the treatment, named regulating the mind and controlling, benefitingand warming, tonifying the kidney and filling up the essence, and promoting the circulation of the governor vessel. Those four therapeutic methods are equally important. Acupuncture, moxibusiton and herbal medicine are applied in combination in the treatment. Additionally, the psychotherapy and rehabilitation are the accessory therapies.

As a common disease in nervous system, epilepsy is possessed of characteristics of high incidence, suddenness and recurrent seizures. Timely prediction with corresponding rescues and treatments can be regarded as effective countermeasure to epilepsy emergencies, while most accidental injuries can thus be avoided. Currently, how to use electroencephalogram (EEG) signals to predict seizure is becoming a highlight topic in epilepsy researches. In spite of significant progress that made, more efforts are still to be made before clinical applications. This paper reviews past epilepsy studies, including research records and critical technologies. Contributions of machine learning (ML) and deep learning (DL) on seizure predictions have been emphasized. Since feature selection and model generalization limit prediction ratings of conventional ML measures, DL based seizure predictions predominate future epilepsy studies. Consequently, more exploration may be vitally important for promoting clinical applications of epileptic seizure prediction.
Electroencephalography ; Epilepsy/diagnosis* ; Humans ; Machine Learning ; Seizures/diagnosis* ; Signal Processing, Computer-Assisted

Arrhythmia is a significant cardiovascular disease that poses a threat to human health, and its primary diagnosis relies on electrocardiogram (ECG). Implementing computer technology to achieve automatic classification of arrhythmia can effectively avoid human error, improve diagnostic efficiency, and reduce costs. However, most automatic arrhythmia classification algorithms focus on one-dimensional temporal signals, which lack robustness. Therefore, this study proposed an arrhythmia image classification method based on Gramian angular summation field (GASF) and an improved Inception-ResNet-v2 network. Firstly, the data was preprocessed using variational mode decomposition, and data augmentation was performed using a deep convolutional generative adversarial network. Then, GASF was used to transform one-dimensional ECG signals into two-dimensional images, and an improved Inception-ResNet-v2 network was utilized to implement the five arrhythmia classifications recommended by the AAMI (N, V, S, F, and Q). The experimental results on the MIT-BIH Arrhythmia Database showed that the proposed method achieved an overall classification accuracy of 99.52% and 95.48% under the intra-patient and inter-patient paradigms, respectively. The arrhythmia classification performance of the improved Inception-ResNet-v2 network in this study outperforms other methods, providing a new approach for deep learning-based automatic arrhythmia classification.
Humans ; Arrhythmias, Cardiac/diagnostic imaging* ; Cardiovascular Diseases ; Algorithms ; Databases, Factual ; Electrocardiography

OBJECTIVES: Shelter hospital was an alternative way to provide large-scale medical isolation and treatment for people with mild coronavirus disease 2019 (COVID-19). Due to various reasons, patients admitted to the large shelter hospital was reported high level of psychological distress, so did the healthcare workers. This study aims to introduce a comprehensive and multifaceted psychosocial crisis intervention model. METHODS: The psychosocial crisis intervention model was provided to 200 patients and 240 healthcare workers in Wuhan Wuchang shelter hospital. Patient volunteers and organized peer support, client-centered culturally sensitive supportive care, timely delivery of scientific information about COVID-19 and its complications, mental health knowledge acquisition of non-psychiatric healthcare workers, group activities, counseling and education, virtualization of psychological intervention, consultation and liaison were exhibited respectively in the model. Pre-service survey was done in 38 patients and 49 healthcare workers using the Generalized Anxiety Disorder 7-item (GAD-7) scale, the Patient Health Questionnaire 2-item (PHQ-2) scale, and the Primary Care PTSD screen for the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (PC-PTSD-5). Forty-eight healthcare workers gave feedback after the intervention. RESULTS: The psychosocial crisis intervention model was successfully implemented by 10 mental health professionals and was well-accepted by both patients and healthcare workers in the shelter hospital. In pre-service survey, 15.8% of 38 patients were with anxiety, 55.3% were with stress, and 15.8% were with depression; 16.3% of 49 healthcare workers were with anxiety, 26.5% were with stress, and 22.4% were with depression. In post-service survey, 62.5% of 48 healthcare workers thought it was very practical, 37.5% thought more practical; 37.5% of them thought it was very helpful to relief anxiety and insomnia, and 27.1% thought much helpful; 37.5% of them thought it was very helpful to recognize patients with anxiety and insomnia, and 29.2% thought much helpful; 35.4% of them thought it was very helpful to deal with patients' anxiety and insomnia, and 37.5% thought much helpful. CONCLUSIONS Psychological crisis intervention is feasible, acceptable, and associated with positive outcomes. Future tastings of this model in larger population and different settings are warranted.
Humans ; COVID-19 ; Sleep Initiation and Maintenance Disorders ; Crisis Intervention ; Psychosocial Intervention ; SARS-CoV-2 ; Mental Health ; Depression/epidemiology* ; Health Personnel/psychology* ; Anxiety/etiology*