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Lower limb motion intention recognition based on sEMG fusion features
P Zhang, J Zhang, A Elsabbagh - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Surface Electromyography (sEMG) has been extensively used for gait analysis and robotic
control. Since the low accuracy of intention recognition limits the development of …
control. Since the low accuracy of intention recognition limits the development of …
Evaluation of Hand Action classification performance using machine learning based on signals from two sEMG electrodes
Classification-based myoelectric control has attracted significant interest in recent years,
leading to prosthetic hands with advanced functionality, such as multi-grip hands. Thus far …
leading to prosthetic hands with advanced functionality, such as multi-grip hands. Thus far …
A Deep Learning‐Based Classification Method for Different Frequency EEG Data
T Wen, Y Du, T Pan, C Huang… - … Mathematical Methods in …, 2021 - Wiley Online Library
In recent years, the research on electroencephalography (EEG) has focused on the feature
extraction of EEG signals. The development of convenient and simple EEG acquisition …
extraction of EEG signals. The development of convenient and simple EEG acquisition …
Automatic hip geometric feature extraction in DXA imaging using regional random forest
BACKGROUND: Hip fracture is considered one of the salient disability factors across the
global population. People with hip fractures are prone to become permanently disabled or …
global population. People with hip fractures are prone to become permanently disabled or …
A Hand Gesture Recognition Strategy Based on Virtual-Dimension Increase of EMG
Y Wang, Y Tian, J Zhu, H She, Y Jiang… - Cyborg and Bionic …, 2024 - spj.science.org
The electromyography (EMG) signal is the biocurrent associated with muscle contraction
and can be used as the input signal to a myoelectric intelligent bionic hand to control …
and can be used as the input signal to a myoelectric intelligent bionic hand to control …
Acceleration of brain cancer detection algorithms during surgery procedures using GPUs
Abstract The HypErspectraL Imaging Cancer Detection (HELICoiD) European project aims
at develo** a methodology for tumor tissue classification through hyperspectral imaging …
at develo** a methodology for tumor tissue classification through hyperspectral imaging …
[PDF][PDF] The Application of Folk Art with Virtual Reality Technology in Visual Communication.
R Zhang, X Zhao - Intelligent Automation & Soft …, 2020 - pdfs.semanticscholar.org
1. Hunan Vocational College of Art Chang Sha 410100, PR China 2. School of Educational
Information Technology, Central China Normal University, Wuhan 430079, PR China 1 …
Information Technology, Central China Normal University, Wuhan 430079, PR China 1 …
[PDF][PDF] CNN-PS: Electroencephalogram Classification of Brain States Using Hybrid Machine-Deep Learning Approach
OA Saltykova - Iraqi Journal For Computer Science and Mathematics, 2023 - iasj.net
Electroencephalography (EEG) has been used for quite some time as a diagnostic
technique in neurology. The goal of this publication is to serve as a resource for researchers …
technique in neurology. The goal of this publication is to serve as a resource for researchers …
Experimental design of lower-limb movement recognition based on support vector machine
As a rehabilitation aid, the lower extremity rehabilitation robot usually works together with
the patient during the rehabilitation training process, and achieves therapeutic effects by …
the patient during the rehabilitation training process, and achieves therapeutic effects by …
Continuous prediction of multi-joint angles based on Informer model using novel fused features
R Wan, Z Zhu, G Cui, S Chen - Measurement Science and …, 2024 - iopscience.iop.org
Continuous prediction of multi-joint angles based on surface electromyography (sEMG) has
the potential to enhance the human-machine interaction performance. However, achieving …
the potential to enhance the human-machine interaction performance. However, achieving …