A5101728062- EEG and Brain-Computer Interfaces
- Spine and Intervertebral Disc Pathology
- Cervical and Thoracic Myelopathy
- Neuroscience and Neural Engineering
- Spinal Fractures and Fixation Techniques
- Gaze Tracking and Assistive Technology
- Neural dynamics and brain function
- ECG Monitoring and Analysis
- Functional Brain Connectivity Studies
- Anesthesia and Pain Management
- Geological Modeling and Analysis
- Industrial Vision Systems and Defect Detection
- Heart Rate Variability and Autonomic Control
- Sleep and Work-Related Fatigue
- Wireless Networks and Protocols
- Image Processing Techniques and Applications
- Advanced Image Processing Techniques
- Surgical Simulation and Training
- Millimeter-Wave Propagation and Modeling
- Optical Systems and Laser Technology
- Musculoskeletal pain and rehabilitation
- Image and Object Detection Techniques
- Forest Ecology and Biodiversity Studies
- Clinical practice guidelines implementation
- Indoor and Outdoor Localization Technologies
China University of Geosciences (Beijing)
2025
Xi'an Polytechnic University
2024
National University of Defense Technology
2021-2023
Yan'an University
2023
North Jersey Brain and Spine Center
2013-2021
Desert Institute For Spine Care
2020
Regional differences in acceptance and utilization of MISST by spine surgeons may have an impact on clinical decision-making the surgical treatment common degenerative conditions lumbar spine. The purpose this study was to analyze various minimally invasive spinal surgery techniques (MISST) world over.The authors solicited responses online survey sent email, chat groups social media networks including Facebook, WeChat, WhatsApp, Linkedin. Surgeons were asked following questions: (I) Do you...
Thoracic disc herniation is a relatively rare yet challenging-to-diagnose condition. Currently there no universally accepted optimal surgical treatment for symptomatic thoracic herniation. Previously reported approaches are often associated with high complication rates. Here we describe our minimally invasive technique of removing herniation, and report the primary results series cases. Between January 2009 March 2012, 13 patients were treated endoscopic foraminotomy discectomy under local...
Brain-controlled wheelchairs are one of the most promising applications that can help people gain mobility after their normal interaction pathways have been compromised by neuromuscular diseases. The feasibility using brain signals to control has well demonstrated healthy in previous studies. However, potential users brain-controlled suffering from severe physical disabilities or who a "locked-in" state. To further validate clinical practicability our previously proposed P300-based...
Background: The optimal PECD surgical approach for cervical intervertebral disc herniation (CIVDH) remains controversial. conventional posterior K-hole leads to damage of facet joint.Objectives: This article is first describe a novel lamina–hole percutaneous endoscopic discectomy (PECD) CIVDH. objective this study evaluate the feasibility and short-term clinical effect approach.Methods: Single-center retrospective observational all patients managed with (PPECD) using symptomatic single-level...
Increases in stand age can significantly change litter and soil microenvironmental properties of plantations. However, how these factors by which pathways they act together to affect decomposition are not well understood. In this study, litters were collected from four Robinia pseudoacacia (Rp) plantations a 10 ∼ 43-year sequence the Loess Plateau (China) used conduct 592-day in-situ experiment using litterbag method. The changes chemical traits, physiochemical environment, microbial...
ABSTRACT The accurate recognition of geological structures in field outcrop images is critical for applications such as hazard analysis, seismic risk assessment, and urban planning. However, traditional manual interpretation time‐consuming, labor‐intensive, subjective, limiting its scalability precision. To address this gap, study proposes an intelligent, automated method based on deep learning techniques. methodology integrates Fourier transform, Canny edge detection, Mask R‐CNN instance...
Background: General anesthesia (GA), which is routinely applied in patients who undergo percutaneous endoscopic interlaminar lumbar discectomy (PEILD) of L5-S1 disc herniation, closely associated with postoperative cognitive dysfunction (POCD) the elderly. Local (LA) an alternative pain control protocol that has not yet been fully evaluated. Objectives: To evaluate feasibility LA PEILD compared GA. Study Design: A retrospective study. Setting: This study took place at First Affiliated...
This study aimed to analyze the motivators and obstacles implementation of minimally invasive spinal surgery techniques (MISST) by surgeons. Motivators detractors may impact availability MISST patients drive spine surgeons' clinical decision-making in treatment common degenerative conditions lumbar spine.The authors solicited responses an online survey sent surgeons email, chat groups social media networks including Facebook, WeChat, WhatsApp, Linkedin. Descriptive statistics were employed...
Brain-controlled wheelchairs (BCWs) are important applications of brain-computer interfaces (BCIs). Currently, most BCWs semiautomatic. When users want to reach a target interest in their immediate environment, this semiautomatic interaction strategy is slow.To end, we combined computer vision (CV) and augmented reality (AR) with BCW proposed the CVAR-BCW: novel automatic strategy. The CVAR-BCW uses translucent head-mounted display (HMD) as user interface, CV automatically detect...
Objective . To compare the difference in clinical and radiographic outcomes between anterior transcorporeal transdiscal percutaneous endoscopic cervical discectomy (ATc-PECD/ATd-PECD) approaches for treating patients with intervertebral disc herniation (CIVDH). Method We selected 77 single-segment CIVDH received ATc-PECD or ATd-PECD Second Affiliated Hospital of Chongqing Medical University March 1, 2010, July 2015. 35 suffered from ATc-PECD, there were 42 group. Obtaining data 3, 6, 12, 24...
Convolutional neural networks (CNNs) have shown great potential in the field of brain-computer interfaces (BCIs) due to their ability directly process raw electroencephalogram (EEG) signals without artificial feature extraction. Some CNNs achieved better classification accuracy than that traditional methods. Raw EEG are usually represented as a two-dimensional (2-D) matrix composed channels and time points, ignoring spatial topological information electrodes. Our goal is make CNN takes...
Abstract Background Current research related to electroencephalogram (EEG)-based driver’s emergency braking intention detection focuses on recognizing from normal driving, with little attention differentiating braking. Moreover, the classification algorithms used are mainly traditional machine learning methods, and inputs manually extracted features. Methods To this end, a novel EEG-based strategy is proposed in paper. The experiment was conducted simulated driving platform three different...
Recognizing in-air gestures can enable intelligent human–computer interaction (HCI) applications and facilitate human lives. However, existing sensor/camera-based methods for gesture recognition are either nonubiquitous, intrusive to privacy, or inconvenient carry around. Contemporary device-free approaches require the person be in line of sight proximity sensing device. This article shows that WiFi signals recognize hand-drawn even when location is nonline-of-sight/beyond walls...
Previous studies have made great efforts to expand the instruction set in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces. However, most systems are limited single persons and by increasing flicker stimulation frequency range or via multiple frequencies sequential coding joint frequency/phase coding. In this article, we propose a multibrain SSVEP paradigm that encodes instructions generated <italic xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Accurately detecting and identifying drivers' braking intention is the basis of man-machine driving. This paper proposed an electroencephalographic (EEG)-based measurement strategy. We used Car Learning to Act (Carla) platform build simulated driving environment. 11 subjects participated in our study, each subject drove a vehicle complete emergency normal tasks. compared EEG topographic maps different situations three classifiers predict subjects' through signals. The results experiment...
Brain-computer interfaces (BCIs) provide novel hands-free interaction strategies. However, the performance of BCIs is affected by user’s mental energy to some extent. In this study, we aimed analyze combined effects decreased and lack sleep on BCI how reduce these effects. We defined low-mental-energy (LME) condition as a sleep. used long period work (>=18 h) induce LME condition, then P300- SSVEP-based tasks were conducted in or normal conditions. Ten subjects recruited study. Each subject...
Brain-computer interfaces (BCIs) were useful in many scenarios; however current computer screen-based BCIs (CS-BCIs) not wearable. We proposed AR-BCI, a BCI combined with augmented reality, which translucent head-mounted display (HMD) was used as the user interface so that users could wear this AR-BCI and see virtual stimuli real environment simultaneously. recruited ten subjects study. Each subject completed predefined tasks (as experiment group) CS-BCI control respectively. accuracies...