A Novel PSO-Based Optimized Lightweight Convolution Neural Network for Movements Recognizing from Multichannel Surface Electromyogram
As the medium of human-computer interaction, it is crucial to correctly and quickly interpret the motion information of surface electromyography (sEMG). Deep learning can recognize a variety of sEMG actions by end-to-end training. However, most of the existing deep learning approaches have complex s...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi-Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/6642463 |