Real-time EMG based pattern recognition control for hand prostheses: A review on existing methods, challenges and future implementation

N Parajuli, N Sreenivasan, P Bifulco, M Cesarelli… - Sensors, 2019 - mdpi.com
Upper limb amputation is a condition that significantly restricts the amputees from performing
their daily activities. The myoelectric prosthesis, using signals from residual stump muscles …

A review of the key technologies for sEMG-based human-robot interaction systems

K Li, J Zhang, L Wang, M Zhang, J Li, S Bao - … Signal Processing and …, 2020 - Elsevier
As physiological signals that are closely related to human motion, surface electromyography
(sEMG) signals have been widely used in human-robot interaction systems (HRISs). Some …

EMGHandNet: A hybrid CNN and Bi-LSTM architecture for hand activity classification using surface EMG signals

NK Karnam, SR Dubey, AC Turlapaty… - Biocybernetics and …, 2022 - Elsevier
Abstract Recently, Convolutional Neural Networks (CNNs) have been used for the
classification of hand activities from surface Electromyography (sEMG) signals. However …

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 …

Surface EMG-based inter-session gesture recognition enhanced by deep domain adaptation

Y Du, W **, W Wei, Y Hu, W Geng - Sensors, 2017 - mdpi.com
High-density surface electromyography (HD-sEMG) is to record muscles' electrical activity
from a restricted area of the skin by using two dimensional arrays of closely spaced …

[HTML][HTML] EMG pattern recognition in the era of big data and deep learning

A Phinyomark, E Scheme - Big Data and Cognitive Computing, 2018 - mdpi.com
The increasing amount of data in electromyographic (EMG) signal research has greatly
increased the importance of develo** advanced data analysis and machine learning …

[PDF][PDF] Bio-robotics research for non-invasive myoelectric neural interfaces for upper-limb prosthetic control: a 10-year perspective review

N Jiang, C Chen, J He, J Meng, L Pan… - National science …, 2023 - academic.oup.com
ABSTRACT A decade ago, a group of researchers from academia and industry identified a
dichotomy between the industrial and academic state-of-the-art in upper-limb prosthesis …

Intelligent EMG pattern recognition control method for upper-limb multifunctional prostheses: advances, current challenges, and future prospects

OW Samuel, MG Asogbon, Y Geng… - Ieee …, 2019 - ieeexplore.ieee.org
Upper-limb amputation imposes significant burden on amputees thereby restricting them
from fully exploring their environments during activities of daily living. The use of intelligent …

[HTML][HTML] EMG-centered multisensory based technologies for pattern recognition in rehabilitation: state of the art and challenges

C Fang, B He, Y Wang, J Cao, S Gao - Biosensors, 2020 - mdpi.com
In the field of rehabilitation, the electromyography (EMG) signal plays an important role in
interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the …

Surface EMG signal classification using ternary pattern and discrete wavelet transform based feature extraction for hand movement recognition

T Tuncer, S Dogan, A Subasi - Biomedical signal processing and control, 2020 - Elsevier
Hands are two of the most crucial organs and they play major role for human activities.
Therefore, amputee people experience many difficulties in daily life. To overcome these …