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International Conference on Information Technology in Bio- and Medical Informatics

ITBAM 2012: Information Technology in Bio- and Medical Informatics pp 166–168Cite as

Computational Sensemaking on Examples of Knowledge Discovery from Neuroscience Data: Towards Enhancing Stroke Rehabilitation

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 7451)

Abstract

Strokes are often associated with persistent impairment of a lower limb. Functional brain mapping is a set of techniques from neuroscience for mapping biological quantities (computational maps) into spatial representations of the human brain as functional cortical tomography, generating massive data. Our goal is to understand cortical reorganization after a stroke and to develop models for optimizing rehabilitation with non-invasive electroencephalography. The challenge is to obtain insight into brain functioning, in order to develop predictive computational models to increase patient outcome. There are many EEG features that still need to be explored with respect to cortical reorganization. In the present work we use independent component analysis, and data visualization mapping as tools for sensemaking. Our results show activity patterns over the sensorimotor cortex, involved in the execution and association of movements; our results further supports the usefulness of inverse mapping methods and generative models for functional brain mapping in the context of non-invasive monitoring of brain activity.

Keywords

  • Knowledge discovery
  • data mining
  • human-computer interaction
  • gait analysis
  • biomedical informatics
  • infomax independent component analysis

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  • DOI: 10.1007/978-3-642-32395-9_13
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Author information

Authors and Affiliations

  1. Institute for Medical Informatics, Statistics & Documentation, Research Unit HCI4MED, Medical University Graz, A-8036, Graz, Austria

    Andreas Holzinger

  2. Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz University of Technology, A-8010, Graz, Austria

    Reinhold Scherer, Martin Seeber, Johanna Wagner & Gernot Müller-Putz

Authors
  1. Andreas Holzinger
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  2. Reinhold Scherer
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  3. Martin Seeber
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  4. Johanna Wagner
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  5. Gernot Müller-Putz
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Ludwig-Maximilians-University, Oettingenstraße 67, 80538, München, Germany

    Christian Böhm

  2. Department of Computer Science, San Jose State University, One Washington Square, 95192-0249, San Jose, CA, USA

    Sami Khuri

  3. Faculty of Electrical Engineering, Department of Cybernetics, Czech Technical University, Technicka 2, 166 27, Prague 6, Czech Republic

    Lenka Lhotská

  4. Istituto di Informatica e Telematica del CNR, Via G. Moruzzi 1, 56124, Pisa, Italy

    M. Elena Renda

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© 2012 Springer-Verlag Berlin Heidelberg

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Holzinger, A., Scherer, R., Seeber, M., Wagner, J., Müller-Putz, G. (2012). Computational Sensemaking on Examples of Knowledge Discovery from Neuroscience Data: Towards Enhancing Stroke Rehabilitation. In: Böhm, C., Khuri, S., Lhotská, L., Renda, M.E. (eds) Information Technology in Bio- and Medical Informatics. ITBAM 2012. Lecture Notes in Computer Science, vol 7451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32395-9_13

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  • DOI: https://doi.org/10.1007/978-3-642-32395-9_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32394-2

  • Online ISBN: 978-3-642-32395-9

  • eBook Packages: Computer ScienceComputer Science (R0)