Brain-machine interface control via reinforcement learning

Jack DiGiovanna; Babak Mahmoudi; Jeremiah Mitzelfelt; Justin C. Sanchez; Jose C. Principe

doi:10.1109/CNE.2007.369726

Brain-machine interface control via reinforcement learning

Jack DiGiovanna, Babak Mahmoudi, Jeremiah Mitzelfelt, Justin C. Sanchez, Jose C. Principe

Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Scopus citations

Abstract

We investigate the capabilities of reinforcement learning (RL) to create a brain-machine interface (BMI) that uses Q(λ) learning to find the functional mapping between neural activity and intended behavior. This paradigm shift is intended to address the issue of paralyzed and amputee patients whom are physically unable to move, which is necessary to train traditional supervised learning BMIs. We created a RLBMI architecture incorporating a rat behavioral paradigm for prosthetic arm control. The performance results show 'proof of concept' that RLBMI can learn the temporal structure of neural signals to control a prosthetic arm.

Original language	English (US)
Title of host publication	Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering
Pages	530-533
Number of pages	4
DOIs	https://doi.org/10.1109/CNE.2007.369726
State	Published - Sep 25 2007
Event	3rd International IEEE EMBS Conference on Neural Engineering - Kohala Coast, HI, United States Duration: May 2 2007 → May 5 2007

Publication series

Name	Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering

Other

Other	3rd International IEEE EMBS Conference on Neural Engineering
Country/Territory	United States
City	Kohala Coast, HI
Period	5/2/07 → 5/5/07

ASJC Scopus subject areas

Biotechnology
Bioengineering
Neuroscience (miscellaneous)

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10.1109/CNE.2007.369726

Cite this

DiGiovanna, J., Mahmoudi, B., Mitzelfelt, J., Sanchez, J. C., & Principe, J. C. (2007). Brain-machine interface control via reinforcement learning. In Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering (pp. 530-533). [4227331] (Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering). https://doi.org/10.1109/CNE.2007.369726

Brain-machine interface control via reinforcement learning. / DiGiovanna, Jack; Mahmoudi, Babak; Mitzelfelt, Jeremiah; Sanchez, Justin C.; Principe, Jose C.

Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering. 2007. p. 530-533 4227331 (Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

DiGiovanna, J, Mahmoudi, B, Mitzelfelt, J, Sanchez, JC & Principe, JC 2007, Brain-machine interface control via reinforcement learning. in Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering., 4227331, Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering, pp. 530-533, 3rd International IEEE EMBS Conference on Neural Engineering, Kohala Coast, HI, United States, 5/2/07. https://doi.org/10.1109/CNE.2007.369726

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Brain-machine interface control via reinforcement learning

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