Non-Invasive Neural Controller
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open in viewerThis project seeks to evaluate alternative means of controlling a prosthetic (in this case, a hand) using electroencephalographic control. The project consists of four methods; an unsure-feedback neural network, a neural network which lets the user know where it assumes the user wants to go, if unsure; a neutrally-iterated tree, which stores a preset list of locations that the user moves between based on how intently they focus on a task; a continuously-trained neural network, which tries to assume the user's hand position and trains relative to that; and a direct neural network, as described above. The selected methods will be compared to determine training efficiency, accuracy, and response time relative to each other on a universal platform.
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Publisher
- Identifier
- E-project-043018-083606
- Advisor
- Year
- 2018
- Date created
- 2018-04-30
- Resource type
- Major
- Rights statement
Relações
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Itens
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Miniatura | Título | Acesso | Embargo Release Date | Ações |
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Non-Invasive_Neural_Controller.pdf | Público | Baixar |
Permanent link to this page: https://digital.wpi.edu/show/t435gf30x