A5100379832- Muscle activation and electromyography studies
- Hand Gesture Recognition Systems
- Advanced Sensor and Energy Harvesting Materials
- Electromagnetic Compatibility and Measurements
- EEG and Brain-Computer Interfaces
- Wireless Signal Modulation Classification
- Blind Source Separation Techniques
- Radar Systems and Signal Processing
- MRI in cancer diagnosis
- Microwave and Dielectric Measurement Techniques
- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Advanced X-ray and CT Imaging
- Geological and Geochemical Analysis
- Image and Signal Denoising Methods
- Full-Duplex Wireless Communications
- Computational Physics and Python Applications
- Tactile and Sensory Interactions
- Earthquake Detection and Analysis
- Speech and Audio Processing
- Radiomics and Machine Learning in Medical Imaging
- Welding Techniques and Residual Stresses
- earthquake and tectonic studies
- Advanced MRI Techniques and Applications
- Advanced Vision and Imaging
Hebei Medical University
2013-2024
Fourth Hospital of Hebei Medical University
2013-2024
China Academy of Space Technology
2019-2023
Zhejiang University
2016-2021
Abstract Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above below zero. Here, we present that patterns inside instantaneous values high-density sEMG enables gesture to be performed merely with signals at specific instant. We introduce concept an image spatially composed from verify...
The surface electromyography (sEMG)-based gesture recognition with deep learning approach plays an increasingly important role in human-computer interaction. Existing architectures are mainly based on Convolutional Neural Network (CNN) architecture which captures spatial information of electromyogram signal. Motivated by the sequential nature signal, we propose attention-based hybrid CNN and RNN (CNN-RNN) to better capture temporal properties signal for problem. Moreover, present a new sEMG...
High-density surface electromyography (HD-sEMG) is to record muscles' electrical activity from a restricted area of the skin by using two dimensional arrays closely spaced electrodes. This technique allows analysis and modelling sEMG signals in both temporal spatial domains, leading new possibilities for studying next-generation muscle-computer interfaces (MCIs). sEMG-based gesture recognition has usually been investigated an intra-session scenario, absence standard benchmark database limits...
Conventionally, gesture recognition based on non-intrusive muscle-computer interfaces required a strongly-supervised learning algorithm and large amount of labeled training signals surface electromyography (sEMG). In this work, we show that temporal relationship sEMG data glove provides implicit supervisory signal for the model. To demonstrate this, present semi-supervised framework with novel Siamese architecture sEMG-based recognition. Specifically, employ auxiliary tasks to learn visual...
Background: With the continuous innovation of magnetic resonance imaging (MRI) hardware and software technology, amide proton transfer-weighted (APTw) has been applied in liver cancer. However, to our knowledge, no study evaluated feasibility a three-dimensional (3D-APTw) sequence for hepatocellular carcinoma (HCC). This thus aimed conduct an image quality assessment 3D-APTw HCC explore its feasibility. Methods: MRI examinations were completed 134 patients with clinically suspected HCC....
The signal in the receiver is mainly a combination of different modulation types due to complex electromagnetic environment, which makes recognition mixed hot topic recent years. In response poor adaptability existing signals methods, this paper proposes new method for based on cyclic spectrum projection and deep neural network. Firstly, through theoretical derivation, we prove feasibility using communication identification. Then, adopt grayscale projections two-dimensional as identifying...
A E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> -E xmlns:xlink="http://www.w3.org/1999/xlink">y</sub> hybrid electric probe for high frequency electromagnetic interference (EMI) measurement was proposed in the paper. The designed to measure Ex and Ey meantime. And its working is up 55 GHz. Four metal sidewalls were used decrease of unwanted fields. In this paper, time domain reflectometry (TDR) optimize impedance matching, which key...
This paper describes a new design of high-frequency differential line for Ex/Hz probe calibration. Both simulation and measurement results show that it can generate pure transverse electromagnetic field up to 30GHz.