Computer vision-based grasp pattern recognition with application to myoelectric control of dexterous hand prosthesis

C Shi, D Yang, J Zhao, H Liu - IEEE Transactions on Neural …, 2020 - ieeexplore.ieee.org
Artificial intelligence provides new feasibilities to the control of dexterous prostheses. To
achieve suitable grasps over various objects, a novel computer vision-based classification …

Artificial perception and semiautonomous control in myoelectric hand prostheses increases performance and decreases effort

J Mouchoux, S Carisi, S Dosen, D Farina… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Dexterous control of upper limb prostheses with multiarticulated wrists/hands is still a
challenge due to the limitations of myoelectric man-machine interfaces. Multiple factors limit …

Decoding the gras** intention from electromyography during reaching motions

I Batzianoulis, NE Krausz, AM Simon… - … of neuroengineering and …, 2018 - Springer
Background Active upper-limb prostheses are used to restore important hand functionalities,
such as gras**. In conventional approaches, a pattern recognition system is trained over a …

Improving internal model strength and performance of prosthetic hands using augmented feedback

AW Shehata, LF Engels, M Controzzi, C Cipriani… - … of neuroengineering and …, 2018 - Springer
Background The loss of an arm presents a substantial challenge for upper limb amputees
when performing activities of daily living. Myoelectric prosthetic devices partially replace lost …

sEMG-Based Robust Recognition of Gras** Postures with a Machine Learning Approach for Low-Cost Hand Control

MC Mora, JV García-Ortiz, J Cerdá-Boluda - Sensors, 2024 - mdpi.com
The design and control of artificial hands remains a challenge in engineering. Popular
prostheses are bio-mechanically simple with restricted manipulation capabilities, as …