An Experimental Platform To Study The Closed-loop Performance Of Brain-machine Interfaces. - Info and Reading Options
By Ejaz, Naveed, Peterson, Kris D. and Krapp, Holger G.
"An Experimental Platform To Study The Closed-loop Performance Of Brain-machine Interfaces." and the language of the book is English.
“An Experimental Platform To Study The Closed-loop Performance Of Brain-machine Interfaces.” Metadata:
- Title: ➤ An Experimental Platform To Study The Closed-loop Performance Of Brain-machine Interfaces.
- Authors: Ejaz, NaveedPeterson, Kris D.Krapp, Holger G.
- Language: English
Edition Identifiers:
- Internet Archive ID: pubmed-PMC3143588
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The Internet Archive:
This article is from <a href="//archive.org/search.php?query=journaltitle%3A%28Journal%20of%20Visualized%20Experiments%20:%20JoVE%29" rel="nofollow">Journal of Visualized Experiments : JoVE</a>.<h2>Abstract</h2>The non-stationary nature and variability of neuronal signals is a fundamental problem in brain-machine interfacing. We developed a brain-machine interface to assess the robustness of different control-laws applied to a closed-loop image stabilization task. Taking advantage of the well-characterized fly visuomotor pathway we record the electrical activity from an identified, motion-sensitive neuron, H1, to control the yaw rotation of a two-wheeled robot. The robot is equipped with 2 high-speed video cameras providing visual motion input to a fly placed in front of 2 CRT computer monitors. The activity of the H1 neuron indicates the direction and relative speed of the robot's rotation. The neural activity is filtered and fed back into the steering system of the robot by means of proportional and proportional/adaptive control. Our goal is to test and optimize the performance of various control laws under closed-loop conditions for a broader application also in other brain machine interfaces.
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"An Experimental Platform To Study The Closed-loop Performance Of Brain-machine Interfaces." is available for download from The Internet Archive in "texts" format, the size of the file-s is: 9.66 Mbs, and the file-s went public at Fri Oct 24 2014.
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