The hand prosthesis that learns from the user | Sebastian Amsüss

It is no wonder that modern hand prostheses are highly sophisticated mechatronic devices: The human hand is a complex tool for manipulation, interaction, and gesticulation. However, to control so many degrees of freedom is a highly challenging task. In this talk, a machine learning approach will be presented to provide a solution: The hand prosthesis that learns from the user!
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[@Mike-513]

Great to see things moving forward with hand prostheses, I am born without my right hand, I guess I'm partial handed, I have my wrist and all carpel bones. However, I can picture and make the hand movements with my right partial hand. I feel all my fingers but my index finger feels like its missing even thought I have no metacarpal bones and digits. I have to disagree with your comment on people that were born without hands can not distinguish the difference. They may not have the tissue or bone structure but never rule people born without limbs out. They just need to work harder to identify. I am about to get my first prosthetic hand, the Michelangelo I favor but with the taska it's a photo finish. What a game changer! very exciting

[@OttobockProfessionals]

Thank you @WeAreDevelopers for sharing this video! We are proud to be part of the #WeAreDevs conference in Vienna and to present
our new #MyoPlus pattern control which works with AI and recognition prosthesis. This enables the user to control his hand prosthesis in an intuitive, smooth way. Follow our developments of the #MyoPlus on our #OttobockProfessionals channel.

[@mahendrapitale5418]

GREAT

[@studytime9465]

It's awesome!!

[@wayneyue1662]

Great job！