25 January 2019

Neural Networks Restore Movement to Paralyzed Limbs

Artificial intelligence is being developed for a wide range of assistive technology tools, from prosthetic hands to better hearing aids. Deep learning models can provide a synthesized voice for individuals with impaired speech, help the blind see, and translate sign language into text. One reason assistive device developers turn to deep learning is because it works well for decoding noisy signals, like electrical activity from the brain.


Using an NVIDIA Quadro GPU, a deep learning neural decoder (the algorithm that translates neural activity into intended command signals) was trained on brain signals from scripted sessions with Burkhart, where he was asked to think about executing specific hand motions. The neural network learned which brain signals corresponded to which desired movements. However, a key challenge in creating robust neural decoding systems is that brain signals vary from day to day.

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