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Computational
models of touch sensation
Neuronal
signals underlie
the sense of touch;
without this feedback, tasks such as picking up a glass would
be
virtually impossible. Our lab seeks to understand how populations of
touch-sensitive mechanoreceptors in the skin encode an object's
features into neuronal signals. Our goals are to advance
neural
prosthetics and surgical robots.
- methodological tools: solid mechanics models
- statistical and differential equations
- systems modeling and data mining
- psychophysical experiments
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Medical
simulators
The design,
construction
and evaluation of medical simulators for
training doctors to detect palpable breast and prostate cancers and
conduct exams, e.g., chest tube insertion.
- methodological tools task and work domain
analysis.
- custom-build electronics, user interfaces,
silicone-elastomers
- graphics coding of force feedback in 3D virtual
reality
- design of experiments and statistical analysis
- models to predict performance
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