Research on sEMG-Based Gesture Recognition by Dual-View Deep Learning

Research on sEMG-Based Gesture Recognition by Dual-View Deep Learning

In the field of human-machine interaction, gesture recognition using sparse multichannel surface electromyography (sEMG) remains a challenge. Based on the Hilbert filling curve, a dual-view multi-scale convolutional neural network (DVMSCNN) is designed to enhance gesture recognition performance in t...

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Bibliographic Details
Main Authors: Yan Zhang, Fan Yang, Qi Fan, Anjie Yang, Xuan Li
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Human–machine interaction
gesture recognition
multi-view learning
Hilbert filling curve
convolutional neural network
Online Access:https://ieeexplore.ieee.org/document/9732991/

Internet

https://ieeexplore.ieee.org/document/9732991/

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