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INTRODUCTION<br>
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We invite contributions to a special session on "Bayesian models for
motor rehabilitation and control" at the International Conference on
NeuroRehabilitation (ICNR2018) that will take place in Pisa (Italy)
from October 16th to 20th, 2018. This session's aim is to bring
together scientists working on theoretical models and engineers
working on rehabilitation and restoration devices.<br>
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More information about the special session at:
<a class="moz-txt-link-freetext" href="http://www.icnr2018.org/special-sessions-2/">http://www.icnr2018.org/special-sessions-2/</a><br>
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ABSTRACT<br>
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Bayesian statistics is a branch of statistics that provides a
principled way of calculating how prior knowledge can be combined
with observations in a statistically optimal way. Numerous studies
have shown that many aspects of human behaviour (e.g. sensorimotor
control) are close to “Bayes’ optimal”. Learning (or re-learning in
the case of rehabilitation) can also be seen as the process of
updating our priors based on new observations. It seems therefore
natural to employ such models not only to describe neural processes
but also to decode them for the purpose of improving the
effectiveness of rehabilitation or for the control of a prosthetic
device. From an implementation point of view, Bayesian models are
also appealing because they may be better suited than other
techniques for dealing with the smaller data sets that are typically
available in biomedical engineering applications.<br>
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This session’s goal is to promote and showcase cutting edge research
in modeling human neuromotor control for the purpose of improving
rehabilitation techniques or designing better control strategies for
actuated prostheses. In particular, this special session is
dedicated to understanding the potential benefits and limitations of
applying Bayesian techniques to such problems. We envision the
session will provide an interdisciplinary platform bringing together
scientists working on theoretical models and engineers working on
rehabilitation and restoration devices. Example topics may include
but are not limited to: Bayesian model averaging, Markov-Chain Monte
Carlo, sequential Monte Carlo, dynamic causal modeling, state-space
modeling, hierarchical Bayesian modeling, non-parametric Bayesian
inference, and their application to the aforementioned biomedical
engineering problems.<br>
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SUBMISSION INSTRUCTIONS<br>
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Please submit your 2-page extended abstract through the Easy Chair
platform (<a class="moz-txt-link-freetext" href="https://easychair.org/conferences/?conf=icnr2018">https://easychair.org/conferences/?conf=icnr2018</a>) before <b>1st
of June 2018</b>.<br>
During the submission process, please select the special session
code "SS1".<br>
Abstracts have to be formatted according to the ICNR2018 template,
which can be downloaded at: <a class="moz-txt-link-freetext" href="http://www.icnr2018.org/call-for-papers">http://www.icnr2018.org/call-for-papers</a><br>
A selection of the contributions will be published on a special
issue on "IEEE Transactions on Neural Systems and Rehabilitation
Engineering".<br>
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CONTACTS<br>
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For information on the special session, please contact Luca Citi
(<a class="moz-txt-link-abbreviated" href="mailto:lciti@essex.ac.uk">lciti@essex.ac.uk</a>)<br>
For more general information about ICNR2018, please contact the
conference organisers at <a class="moz-txt-link-freetext" href="http://www.icnr2018.org/contact/">http://www.icnr2018.org/contact/</a><br>
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