Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

M Santello, M Bianchi, M Gabiccini, E Ricciardi… - Physics of life …, 2016 - Elsevier
The term 'synergy'–from the Greek synergia–means 'working together'. The concept of
multiple elements working together towards a common goal has been extensively used in …

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 …

EMG feature evaluation for improving myoelectric pattern recognition robustness

A Phinyomark, F Quaine, S Charbonnier… - Expert Systems with …, 2013 - Elsevier
In pattern recognition-based myoelectric control, high accuracy for multiple discriminated
motions is presented in most of related literature. However, there is a gap between the …

A survey of sensor fusion methods in wearable robotics

D Novak, R Riener - Robotics and Autonomous Systems, 2015 - Elsevier
Modern wearable robots are not yet intelligent enough to fully satisfy the demands of end-
users, as they lack the sensor fusion algorithms needed to provide optimal assistance and …

A versatile embedded platform for EMG acquisition and gesture recognition

S Benatti, F Casamassima, B Milosevic… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Wearable devices offer interesting features, such as low cost and user friendliness, but their
use for medical applications is an open research topic, given the limited hardware resources …

The role of muscle synergies in myoelectric control: trends and challenges for simultaneous multifunction control

M Ison, P Artemiadis - Journal of neural engineering, 2014 - iopscience.iop.org
Myoelectric control is filled with potential to significantly change human–robot interaction
due to the ability to non-invasively measure human motion intent. However, current control …

Deep neural network approach in EMG-based force estimation for human–robot interaction

H Su, W Qi, Z Li, Z Chen, G Ferrigno… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In the human–robot interaction, especially when hand contact appears directly on the robot
arm, the dynamics of the human arm presents an essential component in human–robot …

sEMG-based gesture recognition with convolution neural networks

Z Ding, C Yang, Z Tian, C Yi, Y Fu, F Jiang - Sustainability, 2018 - mdpi.com
The traditional classification methods for limb motion recognition based on sEMG have been
deeply researched and shown promising results. However, information loss during feature …

Comparison of sEMG-based feature extraction and motion classification methods for upper-limb movement

S Guo, M Pang, B Gao, H Hirata, H Ishihara - sensors, 2015 - mdpi.com
The surface electromyography (sEMG) technique is proposed for muscle activation detection
and intuitive control of prostheses or robot arms. Motion recognition is widely used to map …

Improving the functionality, robustness, and adaptability of myoelectric control for dexterous motion restoration

D Yang, Y Gu, NV Thakor, H Liu - Experimental brain research, 2019 - Springer
The development of advanced and effective human–machine interfaces, especially for
amputees to control their prostheses, is very high priority and a very active area of research …