A5050079548- Muscle activation and electromyography studies
- EEG and Brain-Computer Interfaces
- Inertial Sensor and Navigation
- Stroke Rehabilitation and Recovery
- Prosthetics and Rehabilitation Robotics
- Gait Recognition and Analysis
- Indoor and Outdoor Localization Technologies
- Soft Robotics and Applications
- Neuroscience and Neural Engineering
- Neural Networks and Applications
- Robotics and Sensor-Based Localization
- Non-Invasive Vital Sign Monitoring
- Hand Gesture Recognition Systems
- Robot Manipulation and Learning
- Advanced Sensor and Energy Harvesting Materials
- Energy Efficient Wireless Sensor Networks
- Machine Learning and ELM
- Advanced Memory and Neural Computing
- Blind Source Separation Techniques
- Motor Control and Adaptation
- Anomaly Detection Techniques and Applications
- Advanced Vision and Imaging
- Iterative Learning Control Systems
- Teleoperation and Haptic Systems
- Energy Harvesting in Wireless Networks
University of Leeds
2016-2025
General Hospital of Shenyang Military Region
2025
Bohai University
2023-2024
Sinopec (China)
2024
North University of China
2024
National Engineering Research Center of Electromagnetic Radiation Control Materials
2024
University of Electronic Science and Technology of China
2024
Walter de Gruyter (Germany)
2024
Cardiovascular Institute Hospital
2023-2024
Second Hospital of Hebei Medical University
2018-2024
Musculoskeletal models have been widely used for detailed biomechanical analysis to characterise various functional impairments given their ability estimate movement variables (i.e., muscle forces and joint moments) which cannot be readily measured in vivo. Physics-based computational neuromusculoskeletal can interpret the dynamic interaction between neural drive muscles, dynamics, body kinematics kinetics. Still, such set of solutions suffers from slowness, especially complex models,...
A novel algorithm which combined the merits of clustering strategy and compressive sensing-based (CS-based) scheme was proposed in this paper. The lemmas for relationship between any two adjacent layers, optimal size clusters, distribution cluster head (CH), corresponding proofs were presented first. In addition, to alleviate "hot spot problem" reduce energy consumption resulted from rotation role CHs, a third backup CH (BCH) as well mechanism rotate roles BCH proposed. Subsequently,...
Pneumatic artificial muscles (PAMs) have been widely used in actuation of medical devices due to their intrinsic compliance and high power-to-weight ratio features. However, the nonlinearity time-varying nature PAMs make it challenging maintain high-performance tracking control. In this article, a high-order pseudopartial derivative-based model-free adaptive iterative learning controller (HOPPD-MFAILC) is proposed achieve fast convergence speed. The dynamics PAM converted into dynamic...
Understanding the solid biomechanics of human body is important to study structure and function body, which can have a range applications in health care, sport, well-being, workflow analysis. Conventional laboratory-based biomechanical analysis systems observation-based tests are designed only capture brief snapshots mechanics movement. With recent developments wearable sensing technologies, be conducted less-constrained environments, thus allowing continuous monitoring beyond laboratory...
Feature matters for salient object detection. Existing methods mainly focus on designing a sophisticated structure to incorporate multi-level features and filter out cluttered features. We present Progressive Polishing Network (PFPN), simple yet effective framework progressively polish the be more accurate representative. By employing multiple Modules (FPMs) in recurrent manner, our approach is able detect objects with fine details without any post-processing. A FPM parallelly updates of...
Heterogeneous Graph Neural Networks (HGNNs) have drawn increasing attention in recent years and achieved outstanding performance many tasks. However, despite their wide use, there is currently no understanding of robustness to adversarial attacks. In this work, we first systematically study the HGNNs show that they can be easily fooled by adding edge between target node large-degree (i.e., hub). Furthermore, two key reasons for such vulnerability HGNNs: one perturbation enlargement effect,...
Continuum manipulators can conform to curvilinear paths and manipulate objects in complex environments, which makes it emerging be applied minimally invasive surgery (MIS). However, different controllable operating stiffness of the continuum manipulator is required during stages achieve safe access or stable precise operation. This work proposes an controller (OSC) for typical tendon-driven based on variable impedance control method with Lagrangian dynamic modeling. adjust by modifying...
Large Language Models (LLMs) have shown extraordinary capabilities in understanding and generating text that closely mirrors human communication. However, a primary limitation lies the significant computational demands during training, arising from their extensive parameterization. This challenge is further intensified by dynamic nature of world, necessitating frequent updates to LLMs correct outdated information or integrate new knowledge, thereby ensuring continued relevance. Note many...
This study aims to develop and validate a nomogram based on the Systemic Inflammatory Response Index (SIRI) predict short-term aortic-related adverse events (ARAEs) in patients with acute uncomplicated Type B intramural hematoma (IMH). We retrospectively analyzed 332 diagnosed IMH between April 2018 2024. Patients were categorized into stable group (N=225) exacerbation (N=107) occurrence of ARAEs within 30-day observation period. SIRI was calculated using neutrophil, monocyte, lymphocyte...
Human motion capture technologies have been widely used in a wide spectrum of applications, including interactive game and learning, animation, film special effects, health care, navigation, so on. The existing human techniques, which use structured multiple high-resolution cameras dedicated studio, are complicated expensive. With the rapid development microsensors-on-chip, using wearable microsensors has become an active research topic. Because agility movement, upper-limb estimation...
Internet companies are facing the need for handling large-scale machine learning applications on a daily basis and distributed implementation of algorithms which can handle extra-large-scale tasks with great performance is widely needed. Deep forest recently proposed deep framework uses tree ensembles as its building blocks it has achieved highly competitive results various domains tasks. However, not been tested extremely In this work, based our parameter server system, we developed version...
Traditional rehabilitation techniques have limited effects on the recovery of patients with tetraplegia. A brain–computer interface (BCI) provides an interactive channel that does not depend normal output peripheral nerves and muscles. In this paper, integrated framework a noninvasive electroencephalogram (EEG)-based BCI functional electrical stimulation (FES) is established, which can potentially enable upper limbs to achieve more effective motor rehabilitation. The EEG signals based...
A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted this article. First, a novel generic mathematical definition of Energy Efficiency (EE) proposed, which takes acquisition rate valid data, total consumption, and network lifetime WSNs into consideration simultaneously. To best our knowledge, first time EE mathematically defined. The consumption characteristics each individual...
Small and Medium-sized Enterprises (SMEs) are playing a vital role in the modern economy. Recent years, financial risk analysis for SMEs attracts lots of attentions from institutions. However, usually suffers data deficiency problem, especially mobile institutions which seldom collect credit-related directly SMEs. Fortunately, although information is hard to be acquired sufficiently, interactive relationships between SMEs, may contain valuable risk, available Finding out relationship SME...
EMG-based continuous wrist joint motion estimation has been identified as a promising technique with huge potential in assistive robots. Conventional data-driven model-free methods tend to establish the relationship between EMG signal and using machine learning or deep techniques, but cannot interpret functional neuro-commands relevant motion. In this paper, an EMG-driven musculoskeletal model is proposed estimate This interprets muscle activation levels from signals. A muscle-tendon...
In this paper, an intelligent data-driven optimization scheme is proposed for finding the proper burden surface distribution, which exerts large influences on keeping blast furnace running smoothly in energy-efficient state. scheme, production indicators prediction models are first developed using a kernel extreme learning machine algorithm. To heel, decision presented as multiobjective problem time and solved by modified two-stage strategy to generate initial setting values of surface....
An optimal mission assignment and path planning method of multiple unmanned aerial vehicles (UAVs) for disaster rescue is proposed. In this application, the UAVs include drug delivery UAV, image collection communication relay UAV. When implementing modeling simulation, first, three threat sources are built: weather source, transmission tower upland source. Second, a cost-revenue function constructed. The flight distance, oil consumption, descriptions source factors above considered. analytic...