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Computer vision-based grasp pattern recognition with application to myoelectric control of dexterous hand prosthesis
Artificial intelligence provides new feasibilities to the control of dexterous prostheses. To
achieve suitable grasps over various objects, a novel computer vision-based classification …
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
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 …
challenge due to the limitations of myoelectric man-machine interfaces. Multiple factors limit …
Decoding the gras** intention from electromyography during reaching motions
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 …
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
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 …
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 …
prostheses are bio-mechanically simple with restricted manipulation capabilities, as …