Connectivity Analysis as a Novel Approach to Motor Decoding for Prosthesis Control

@article{Benz2012ConnectivityAA,
  title={Connectivity Analysis as a Novel Approach to Motor Decoding for Prosthesis Control},
  author={Heather L. Benz and Huaijian Zhang and A. Bezerianos and Soumyadipta Acharya and Nathan E. Crone and Xioaxiang Zheng and N. V. Thakor},
  journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},
  year={2012},
  volume={20},
  pages={143-152}
}
The use of neural signals for prosthesis control is an emerging frontier of research to restore lost function to amputees and the paralyzed. Electrocorticography (ECoG) brain-machine interfaces (BMI) are an alternative to EEG and neural spiking and local field potential BMI approaches. Conventional ECoG BMIs rely on spectral analysis at specific electrode sites to extract signals for controlling prostheses. We compare traditional features with information about the connectivity of an ECoG… CONTINUE READING
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