NathanLeroux-git/OnlineTransformerWithSpikingNeurons
This code is the implementation of the Spiking Online Transformer of the paper "Online Transformers with Spiking Neurons for Fast Prosthetic Hand Control". It predicts finger position using a surface Elecromyography regression.
This project helps researchers and engineers develop and test advanced prosthetic hand controls. It takes surface Electromyography (sEMG) data from a user's arm and outputs predictions for individual finger movements, enabling more natural and responsive prosthetic control. It's designed for bioengineers and neuroscientists working on human-machine interfaces.
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Use this if you are developing or evaluating new algorithms for prosthetic hand control based on sEMG signals.
Not ideal if you are looking for a ready-to-use, off-the-shelf prosthetic control system for clinical application.
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Python
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Feb 03, 2025
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