Nov 15, 2016 · We present that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition to be performed merely with sEMG signals at a ...

Oct 8, 2020 · The CNN model effectively solves the limitations of traditional machine learning in sEMG gesture recognition, and combines 1-dim convolution ...

This study puts forward a novel deep learning classifier framework which leverages the potentials of variational mode decomposition (VMD) technique and a ...

The CNN model effectively solves the limitations of traditional machine learning in sEMG gesture recognition, and combines 1‐dim convolution kernel to extract ...

In this paper, we present a comprehensive survey on sEMG-based hand gesture recognition. We provide an overview of the basic knowledge and background of sEMG ...

Jul 9, 2024 · The surface electromyographic (sEMG) signals reflect human motor intention and can be utilized for human-machine interfaces (HMI).

It is presented that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition to be performed merely with s EMG signals ...

This systematic literature review analyses the state-of-the-art of real-time hand gesture recognition models using EMG data and machine learning.

This paper analyzes the applicability and efficiency of DL in sEMG-based gesture recognition and reviews the key techniques of DL-based sEMG pattern recognition ...

Sep 27, 2024 · In this study, we introduced a novel system for processing surface electromyography (sEMG) signals in order to recognize hand gestures. It uses ...