Source:http://linkedlifedata.com/resource/pubmed/id/17377231
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:dateCreated |
2007-3-22
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| pubmed:abstractText |
Current uses of haptic hardware such as the Phantom Premium 6DOF for surgical simulators lack the desired interface transparency and could cause artefacts in the training regime of a student training on a simulator. This problem is addressed and two neural networks are used to find a mapping between handle coordinates and orientation and force output required to counteract gravitational forces. A close fit to the data is achieved for both networks (errors of 0.00149 and 0.0157 between training and predicted forces) and 3DOF gravity compensation is achieved. A 6DOF simulator is created but requires further work to improve it accuracy.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
T
|
| pubmed:status |
MEDLINE
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| pubmed:issn |
0926-9630
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:volume |
125
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
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| pubmed:pagination |
43-8
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| pubmed:dateRevised |
2008-11-21
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| pubmed:meshHeading |
pubmed-meshheading:17377231-Computer Simulation,
pubmed-meshheading:17377231-General Surgery,
pubmed-meshheading:17377231-Gravitation,
pubmed-meshheading:17377231-Great Britain,
pubmed-meshheading:17377231-Humans,
pubmed-meshheading:17377231-Neural Networks (Computer),
pubmed-meshheading:17377231-Software
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| pubmed:year |
2007
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| pubmed:articleTitle |
A 6DOF gravity compensation scheme for a phantom premium using a neural network.
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| pubmed:affiliation |
School of Computing, University of Leeds, UK. matthewb@comp.leeds.ac.uk
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| pubmed:publicationType |
Journal Article
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