Review of sEMG for robot control: Techniques and applications

T Song, Z Yan, S Guo, Y Li, X Li, F Xi - Applied Sciences, 2023 - mdpi.com
Surface electromyography (sEMG) is a promising technology that can capture muscle
activation signals to control robots through novel human–machine interfaces (HMIs). This …

Tinyradarnn: Combining spatial and temporal convolutional neural networks for embedded gesture recognition with short range radars

M Scherer, M Magno, J Erb, P Mayer… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
This work proposes a low-power high-accuracy embedded hand-gesture recognition
algorithm targeting battery-operated wearable devices using low-power short-range RADAR …

A transfer learning model for gesture recognition based on the deep features extracted by CNN

Y Zou, L Cheng - IEEE Transactions on Artificial Intelligence, 2021 - ieeexplore.ieee.org
The surface electromyogram (sEMG) based hand gesture recognition is prevalent in human–
computer interface systems. However, the generalization of the recognition model does not …

Interference-robust millimeter-wave radar-based dynamic hand gesture recognition using 2D CNN-transformer networks

B Jin, X Ma, Z Zhang, Z Lian… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Dynamic gesture recognition using millimeter-wave radar has a broad application prospect
in the industrial Internet of Things (IoT) field. However, the existing methods in the random …

Improving the robustness and adaptability of sEMG-based pattern recognition using deep domain adaptation

P Shi, X Zhang, W Li, H Yu - IEEE journal of biomedical and …, 2022 - ieeexplore.ieee.org
The pattern recognition (PR) based on surface electromyography (sEMG) could improve the
quality of daily life of amputees. However, the lack of robustness and adaptability hinders its …

A wave-shaped electrode flexible sensor capable of sensitively responding to wrinkle excitation for a multifunctional human–computer interaction system

Y Chen, Z Wu, C Han, Z Cao, Y Hu, P Zhao, Y Wang - Nano Research, 2024 - Springer
Human–machine interactions (HMIs) have advanced rapidly in recent decades in the fields
of healthcare, work, and life. However, people with disabilities and other mobility problems …

Gaze-aware hand gesture recognition for intelligent construction

X Wang, D Veeramani, Z Zhu - Engineering Applications of Artificial …, 2023 - Elsevier
The advances in construction robotics in recent decades has been a powerful driver of
construction automation. User-friendly interfaces to support human–robot work collaboration …

Wearable sensors-based hand gesture recognition for human–robot collaboration in construction

X Wang, D Veeramani, Z Zhu - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
The development of robotic machines has shown the potential to promote automation in
construction. One of the critical enablers of human–robot collaboration is a user-friendly …

Integration of Convolutional Neural Network and Vision Transformer for gesture recognition using sEMG

X Liu, L Hu, L Tie, L Jun, X Wang, X Liu - Biomedical Signal Processing …, 2024 - Elsevier
Currently, gesture recognition primarily utilizes Convolutional Neural Networks (CNNs) and
Recurrent Neural Networks (RNNs) among deep learning methods. However, the unique …

Gesture recognition of sEMG signal based on GASF-LDA feature enhancement and adaptive ABC optimized SVM

R Fu, B Zhang, H Liang, S Wang, Y Wang… - … Signal Processing and …, 2023 - Elsevier
The surface EMG signal (sEMG) is the potential signal produced by human muscle
movement, which is closely related to the movement pattern of the limb and widely used in …