Lightweight Deep Learning for sEMG-Based Fingers Position Classification and Embedded System Deployment
This paper presents a lightweight deep learning approach for classifying and tracking finger positions based on surface electromyography (sEMG) signals, designed with a perspective of its implementation in embedded systems. Unlike traditional studies that focus on static hand gestures, this research...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10904232/ |
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