DeepTPA-Net: A Deep Triple Attention Network for sEMG-Based Hand Gesture Recognition
Author:
Affiliation:
1. Department of Computer and Information Sciences, Towson University, Towson, MD, USA
2. Department of Computer Science and Engineering, New Mexico Institute of Mining and Technology, Socorro, NM, USA
Funder
National Science Foundation
Institute for Complex Additive Systems Analysis (ICASA) of the New Mexico Institute of Mining and Technology
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
https://ieeexplore.ieee.org/ielam/6287639/10005208/10239379-aam.pdf
Reference55 articles.
1. Using sample entropy for automated sign language recognition on sEMG and accelerometer data
2. Fuzzy Approximate Entropy Analysis of Chaotic and Natural Complex Systems: Detecting Muscle Fatigue Using Electromyography Signals
3. Recognition of grasp types through principal components of DWT based EMG features
4. sEMG-Based Gesture Recognition with Convolution Neural Networks
5. LSTM Recurrent Neural Network for Hand Gesture Recognition Using EMG Signals
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