An Energy-Efficient Spiking Neural Network for Finger Velocity Decoding for Implantable Brain-Machine Interface. (arXiv:2210.06287v1 [eess.SP])

Brain-machine interfaces (BMIs) are promising for motor rehabilitation and
mobility augmentation. High-accuracy and low-power algorithms are required to
achieve implantable BMI systems. In this paper, we propose a novel spiking
neural network (SNN) decoder for implantable BMI regression tasks. The SNN is
trained with enhanced spatio-temporal backpropagation to fully leverage its
ability in handling temporal problems. The proposed SNN decoder achieves the
same level of correlation coefficient as the state-of-the-art ANN decoder in
offline finger velocity decoding tasks, while it …

arxiv brain energy machine network neural network spiking neural network