What if you could control any device using only subtle hand movements?
New research from Meta’s Reality Labs is pointing even more firmly toward wrist-worn devices using surface electromyography (sEMG) becoming the future of human-computer interaction.
But how do you develop a wrist-worn input device that works for everyone?
Generalization has been one of the most significant challenges in the field of human-computer interaction (HCI). The machine learning models that power a device can be trained to respond to an individual’s hand gestures, but they struggle to apply that same learning to someone else. Essentially, novel HCI devices are usually one-size-fits-one.
On the latest episode of the Meta Tech Podcast, Pascal Hartig sits down with Sean B., Lauren G., and Jesse M. — research scientists on Meta’s EMG engineering and research team — to discuss how their team is tackling the challenge of generalization and reimagining how we interact with technology.
They discuss the road to creating a first-of-its-kind, generic human-computer neuromotor interface, what happens when software and hardware engineering meet neuroscience, and more!
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The Meta Tech Podcast is a podcast, brought to you by Meta, where we highlight the work Meta’s engineers are doing at every level – from low-level frameworks to end-user features.
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