MyoBit: A Public Dataset Based on An Armband with 16 sEMG Channels for Gesture Recognition under Non-ideal Conditions
Author:
Affiliation:
1. Beijing Institute of Technology,Laboratory of Photonics Information Technology,Beijing,China
2. Beijing Institute of Technology,School of Integrated Circuits and Electronics,Beijing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10242389/10242390/10242547.pdf?arnumber=10242547
Reference21 articles.
1. Locomo-Net: A Low -Complex Deep Learning Framework for sEMG-Based Hand Movement Recognition for Prosthetic Control
2. Exploration of Feature Extraction Methods and Dimension for sEMG Signal Classification
3. Adaptive Electrode Calibration Method Based on Muscle Core Activation Regions and Its Application in Myoelectric Pattern Recognition
4. Are armband sEMG devices dense enough for long-term use?—Sensor placement shifts cause significant reduction in recognition accuracy
5. High-Density Surface EMG-Based Gesture Recognition Using a 3D Convolutional Neural Network
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