A review on electromyography decoding and pattern recognition for human-machine interaction

M Simao, N Mendes, O Gibaru, P Neto - Ieee Access, 2019 - ieeexplore.ieee.org
This paper presents a literature review on pattern recognition of electromyography (EMG)
signals and its applications. The EMG technology is introduced and the most relevant …

A review of algorithm & hardware design for AI-based biomedical applications

Y Wei, J Zhou, Y Wang, Y Liu, Q Liu… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
This paper reviews the state of the arts and trends of the AI-Based biomedical processing
algorithms and hardware. The algorithms and hardware for different biomedical applications …

Feature extraction and selection for myoelectric control based on wearable EMG sensors

A Phinyomark, R N. Khushaba, E Scheme - Sensors, 2018 - mdpi.com
Specialized myoelectric sensors have been used in prosthetics for decades, but, with recent
advancements in wearable sensors, wireless communication and embedded technologies …

Electromyogram-based classification of hand and finger gestures using artificial neural networks

KH Lee, JY Min, S Byun - Sensors, 2021 - mdpi.com
Electromyogram (EMG) signals have been increasingly used for hand and finger gesture
recognition. However, most studies have focused on the wrist and whole-hand gestures and …

[HTML][HTML] Machine learning-based feature extraction and classification of emg signals for intuitive prosthetic control

CL Kok, CK Ho, FK Tan, YY Koh - Applied Sciences, 2024 - mdpi.com
Signals play a fundamental role in science, technology, and communication by conveying
information through varying patterns, amplitudes, and frequencies. This paper introduces …

An experimental study on upper limb position invariant EMG signal classification based on deep neural network

AK Mukhopadhyay, S Samui - Biomedical signal processing and control, 2020 - Elsevier
The classification of surface electromyography (sEMG) signal has an important usage in the
man-machine interfaces for proper controlling of prosthetic devices with multiple degrees of …

EMG feature selection and classification using a Pbest-guide binary particle swarm optimization

J Too, AR Abdullah, N Mohd Saad, W Tee - Computation, 2019 - mdpi.com
Due to the increment in hand motion types, electromyography (EMG) features are
increasingly required for accurate EMG signals classification. However, increasing in the …

A bionic hand controlled by hand gesture recognition based on surface EMG signals: A preliminary study

WT Shi, ZJ Lyu, ST Tang, TL Chia, CY Yang - … and Biomedical Engineering, 2018 - Elsevier
A bionic hand with fine motor ability could be a favorable option for replacing the human
hand when performing various operations. Myoelectric control has been widely used to …

Current trends and confounding factors in myoelectric control: Limb position and contraction intensity

E Campbell, A Phinyomark, E Scheme - Sensors, 2020 - mdpi.com
This manuscript presents a hybrid study of a comprehensive review and a systematic
(research) analysis. Myoelectric control is the cornerstone of many assistive technologies …

Surface EMG based continuous estimation of human lower limb joint angles by using deep belief networks

J Chen, X Zhang, Y Cheng, N ** - Biomedical Signal Processing and …, 2018 - Elsevier
Surface electromyography (EMG) signals have been widely used in locomotion studies and
human-machine interface applications. In this paper, a regression model which relates the …