LogInIt should aim in restoring dexterity for fine tasks.
I never learned to play piano and I applaud those who mastered this fine art. Unfortunately, sometimes life gets in your way and makes it impossible to do what you always liked. This is when various technologies emerge.
Researchers have presented a prototype of a soft robotic hand exoskeleton that uses machine-learning algorithms to help individuals, especially those who have suffered from a stroke, relearn how to play piano "by ‘feeling’ the difference between correct and incorrect versions of the same song."
"The exoskeleton features piezoresistive sensor arrays with 16 taxels integrated into each fingertip. The hand exoskeleton was created as a single unit, with polyvinyl acid (PVA) used as a stent and later dissolved to construct the internal pressure chambers for the five individually actuated digits."
There were ten variations of a song produced, one was correct and nine contained rhythmic errors. The glove was worn by a person and trained to find differences between correct and incorrect versions of the song. As a result, "the ANN algorithm had the highest classification accuracy of 97.13% ± 2.00% with the human subject and 94.60% ± 1.26% without."
The glove is soft and flexible, weighs 191g (6.7oz), and can be custom-made to fit anyone.
“While wearing the glove, human users have control over the movement of each finger to a significant extent,” said senior author Dr Erik Engeberg, a professor at Florida Atlantic University’s Department of Ocean & Mechanical Engineering. “The glove is designed to assist and enhance their natural hand movements, allowing them to control the flexion and extension of their fingers. The glove supplies hand guidance, providing support and amplifying dexterity.”
This glove is meant to help people with reduced limb functionality complete tasks that require fine motor skills and can potentially be used in other areas. It is by no means perfect yet: its accuracy and reliability of tactile sensing can be improved, "enhancing the adaptability and dexterity of the exoskeleton design, and refining the machine learning algorithms to better interpret and respond to user input."
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