An efficient surface electromyography-based gesture recognition algorithm based on multiscale fusion convolution and channel attention
Abstract In the field of rehabilitation, although deep learning have been widely used in multitype gesture recognition via surface electromyography (sEMG), their higher algorithmic complexity often leads to low computationally inefficient, which compromise their practicality. To achieve more efficie...
Saved in:
| Main Authors: | Bin Jiang, Hao Wu, Qingling Xia, Hanguang Xiao, Bo Peng, Li Wang, Yun Zhao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-12-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-81369-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Electromyography-Based Gesture Recognition With Explainable AI (XAI): Hierarchical Feature Extraction for Enhanced Spatial-Temporal Dynamics
by: Jungpil Shin, et al.
Published: (2025-01-01) -
Gesture-controlled reconfigurable metasurface system based on surface electromyography for real-time electromagnetic wave manipulation
by: Chen Junzai, et al.
Published: (2025-01-01) -
Dynamic Hypergraph Convolutional Networks for Hand Motion Gesture Sequence Recognition
by: Dong-Xing Jing, et al.
Published: (2025-06-01) -
A multi-channel bioimpedance-based device for Vietnamese hand gesture recognition
by: Nhat-Minh Than, et al.
Published: (2024-12-01) -
On the Deployment of Edge AI Models for Surface Electromyography-Based Hand Gesture Recognition
by: Andres Gomez-Bautista, et al.
Published: (2025-05-01)