Research graph
References from Overcoming behavioral variability in electromyography signals by an adaptive incremental classification approach. Local targets link to admitted publications; unresolved targets remain external evidence.
Improving the accuracy of hand sign recognition by chaotic swarm algorithm-based feature selection applied to fused surface electromyography and force myography signals
10.1016/j.engappai.2025.110878 · 2025 · External reference
Semg-based gesture classifier for a rehabilitation glove
10.3389/fnbot.2022.750482 · 2022 · External reference
User-independent EMG gesture recognition method based on adaptive learning
10.3389/fnins.2022.847180 · 2022 · External reference
10.1017/s0954422421000135
10.1017/s0954422421000135 · External reference
Alcohol consumption and measures of sarcopenic muscle risk: cross-sectional and prospective associations within the UK Biobank study
10.1007/s00223-023-01081-4 · 2023 · External reference
The effects of acute alcohol consumption and eccentric muscle damage on neuromuscular function
10.1139/h11-137 · 2012 · External reference
Improvement of EMG pattern recognition model performance in repeated uses by combining feature selection and incremental transfer learning
10.3389/fnbot.2021.699174 · 2021 · External reference
On-line SEMG hand gesture recognition based on incremental adaptive learning
2019 · External reference
Surface EMG-based inter-session gesture recognition enhanced by deep domain adaptation
10.3390/s17030458 · 2017 · External reference
Subject-independent SEMG pattern recognition by using a muscle source activation model
10.1109/lra.2020.3006824 · 2020 · External reference
10.1109/10.204774
10.1109/10.204774 · External reference
Self-recalibrating surface EMG pattern recognition for neuroprosthesis control based on convolutional neural network
10.3389/fnins.2017.00379 · 2017 · External reference
Unresolved reference
2023 · External reference
Gesture recognition by instantaneous surface EMG images
10.1038/srep36571 · 2016 · External reference
Hand gesture recognition using compact CNN via surface electromyography signals
10.3390/s20030672 · 2020 · External reference
Characterization of a benchmark database for myoelectric movement classification
10.1109/tnsre.2014.2328495 · 2014 · External reference
Determination of parameters of quaternion signal transformation using filtering results
10.1134/s1054661808030176 · 2023 · External reference
10.1109/tnsre.2020.2966749
10.1109/tnsre.2020.2966749 · External reference
An incremental learning based gesture recognition system for consumer devices using edge-fog computing
10.1109/tce.2019.2961066 · 2020 · External reference
Unresolved reference
2023 · External reference
User-independent hand gesture recognition classification models using sensor fusion
10.3390/s22041321 · 2022 · External reference
10.3390/s19132846
10.3390/s19132846 · External reference
A method for stress detection using Empatica E4 bracelet and machine-learning techniques
10.3390/s23073565 · 2023 · External reference
10.3390/s24113638
10.3390/s24113638 · External reference
A systematic review of EMG applications for the characterization of forearm and hand muscle activity during activities of daily living: results, challenges, and open issues
10.3390/s21093035 · 2021 · External reference
Techniques of EMG signal analysis: detection, processing, classification and applications
10.1251/bpo115 · 2006 · External reference
10.1109/iwis61214.2023.10302762
10.1109/iwis61214.2023.10302762 · 2023 · External reference
A deep transfer learning approach to reducing the effect of electrode shift in EMG pattern recognition-based control
10.1109/tnsre.2019.2962189 · 2019 · External reference
