Cargando…

Multi-Category Gesture Recognition Modeling Based on sEMG and IMU Signals

Gesture recognition based on wearable devices is one of the vital components of human–computer interaction systems. Compared with skeleton-based recognition in computer vision, gesture recognition using wearable sensors has attracted wide attention for its robustness and convenience. Recently, many...

Descripción completa

Detalles Bibliográficos
Autores principales:	Jiang, Yujian, Song, Lin, Zhang, Junming, Song, Yang, Yan, Ming
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371015/ https://www.ncbi.nlm.nih.gov/pubmed/35957417 http://dx.doi.org/10.3390/s22155855

Ejemplares similares

Improved Multi-Stream Convolutional Block Attention Module for sEMG-Based Gesture Recognition
por: Wang, Shudi, et al.
Publicado: (2022)

Hand Gesture Recognition Using EMG-IMU Signals and Deep Q-Networks
por: Vásconez, Juan Pablo, et al.
Publicado: (2022)

Dataset for multi-channel surface electromyography (sEMG) signals of hand gestures
por: Ozdemir, Mehmet Akif, et al.
Publicado: (2022)

sEMG-Based Hand Gesture Recognition Using Binarized Neural Network
por: Kang, Soongyu, et al.
Publicado: (2023)

A novel hand gesture recognition method based on 2-channel sEMG
por: Yu, Hailong, et al.
Publicado: (2018)

LST-EMG-Net: Long short-term transformer feature fusion network for sEMG gesture recognition
por: Zhang, Wenli, et al.
Publicado: (2023)

sEMG-Based Neural Network Prediction Model Selection of Gesture Fatigue and Dataset Optimization
por: Ma, Fujun, et al.
Publicado: (2020)

Simultaneous sEMG Classification of Hand/Wrist Gestures and Forces
por: Leone, Francesca, et al.
Publicado: (2019)

sEMG-Based Gesture Classifier for a Rehabilitation Glove
por: Copaci, Dorin, et al.
Publicado: (2022)

Enhanced Performance for Multi-Forearm Movement Decoding Using Hybrid IMU–sEMG Interface
por: Shahzad, Waseem, et al.
Publicado: (2019)

Application Research on Optimization Algorithm of sEMG Gesture Recognition Based on Light CNN+LSTM Model
por: Bai, Dianchun, et al.
Publicado: (2021)

Biometric From Surface Electromyogram (sEMG): Feasibility of User Verification and Identification Based on Gesture Recognition
por: He, Jiayuan, et al.
Publicado: (2020)

Feature–Classifier Pairing Compatibility for sEMG Signals in Hand Gesture Recognition under Joint Effects of Processing Procedures
por: Asfour, Mohammed, et al.
Publicado: (2022)

A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition
por: Hu, Yu, et al.
Publicado: (2018)

A novel concatenate feature fusion RCNN architecture for sEMG-based hand gesture recognition
por: Xu, Pufan, et al.
Publicado: (2022)

Reducing the Energy Consumption of sEMG-Based Gesture Recognition at the Edge Using Transformers and Dynamic Inference
por: Xie, Chen, et al.
Publicado: (2023)

Empowering Hand Rehabilitation with AI-Powered Gesture Recognition: A Study of an sEMG-Based System
por: Guo, Kai, et al.
Publicado: (2023)

Improved Network and Training Scheme for Cross-Trial Surface Electromyography (sEMG)-Based Gesture Recognition
por: Dai, Qingfeng, et al.
Publicado: (2023)

sEMG-Based Hand-Gesture Classification Using a Generative Flow Model
por: Sun, Wentao, et al.
Publicado: (2019)

Voiceless Bangla vowel recognition using sEMG signal
por: Mostafa, S. S., et al.
Publicado: (2016)

A Low-Cost, Wireless, 3-D-Printed Custom Armband for sEMG Hand Gesture Recognition
por: Côté-Allard, Ulysse, et al.
Publicado: (2019)

Selection of the Best Set of Features for sEMG-Based Hand Gesture Recognition Applying a CNN Architecture
por: Sandoval-Espino, Jorge Arturo, et al.
Publicado: (2022)

Compound motion decoding based on sEMG consisting of gestures, wrist angles, and strength
por: Zhang, Xiaodong, et al.
Publicado: (2022)

Hierarchical strategy for sEMG classification of the hand/wrist gestures and forces of transradial amputees
por: Leone, Francesca, et al.
Publicado: (2023)

Feature Fusion-Based Improved Capsule Network for sEMG Signal Recognition
por: Wang, Wanliang, et al.
Publicado: (2022)

Multi-modality deep forest for hand motion recognition via fusing sEMG and acceleration signals
por: Fang, Yinfeng, et al.
Publicado: (2022)

Preliminary Study on Continuous Recognition of Elbow Flexion/Extension Using sEMG Signals for Bilateral Rehabilitation
por: Song, Zhibin, et al.
Publicado: (2016)

A Smartphone-Based sEMG Signal Analysis System for Human Action Recognition
por: Yu, Shixin, et al.
Publicado: (2023)

Dynamic Gesture Recognition Using Surface EMG Signals Based on Multi-Stream Residual Network
por: Yang, Zhiwen, et al.
Publicado: (2021)

Elements Influencing sEMG-Based Gesture Decoding: Muscle Fatigue, Forearm Angle and Acquisition Time
por: Qing, Zengyu, et al.
Publicado: (2021)

Gesture recognition by instantaneous surface EMG images
por: Geng, Weidong, et al.
Publicado: (2016)

An sEMG-Controlled 3D Game for Rehabilitation Therapies: Real-Time Time Hand Gesture Recognition Using Deep Learning Techniques
por: Nasri, Nadia, et al.
Publicado: (2020)

sEMG dataset of routine activities
por: Khan, Asad Mansoor, et al.
Publicado: (2020)

EOG-sEMG Human Interface for Communication
por: Tamura, Hiroki, et al.
Publicado: (2016)

sEMG-Based Trunk Compensation Detection in Rehabilitation Training
por: Ma, Ke, et al.
Publicado: (2019)

IMU Sensor-Based Hand Gesture Recognition for Human-Machine Interfaces
por: Kim, Minwoo, et al.
Publicado: (2019)

Fusion Learning for sEMG Recognition of Multiple Upper-Limb Rehabilitation Movements
por: Zhong, Tianyang, et al.
Publicado: (2021)

The Influence of the sEMG Amplitude Estimation Technique on the EMG–Force Relationship
por: Ranaldi, Simone, et al.
Publicado: (2022)

Liquid Metal Flexible EMG Gel Electrodes for Gesture Recognition
por: Bai, Yanru, et al.
Publicado: (2023)

Multimodal hand gesture recognition using single IMU and acoustic measurements at wrist
por: Siddiqui, Nabeel, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_k4kq9qlqnthkl4tvreaopi0dkg