Explore the words cloud of the MoreGrasp project. It provides you a very rough idea of what is the project "MoreGrasp" about.
The following table provides information about the project.
TECHNISCHE UNIVERSITAET GRAZ
|Coordinator Country||Austria [AT]|
|Total cost||3˙471˙452 €|
|EC max contribution||3˙471˙452 € (100%)|
1. H2020-EU.184.108.40.206. (Content technologies and information management: ICT for digital content, cultural and creative industries)
|Duration (year-month-day)||from 2015-03-01 to 2018-05-31|
Take a look of project's partnership.
|1||TECHNISCHE UNIVERSITAET GRAZ||AT (GRAZ)||coordinator||675˙120.00|
|2||UNIVERSITATSKLINIKUM HEIDELBERG||DE (HEIDELBERG)||participant||682˙687.00|
|3||UNIVERSITY OF GLASGOW||UK (GLASGOW)||participant||626˙010.00|
|4||BIT & BRAIN TECHNOLOGIES SL||ES (ZARAGOZA)||participant||593˙986.00|
|5||KNOW-CENTER GMBH RESEARCH CENTER FOR DATA-DRIVEN BUSINESS & BIG DATA ANALYTICS||AT (GRAZ)||participant||558˙579.00|
|6||Medel Medizinische Elektronic Handelsgesellschaft mbH||DE (Hamburg)||participant||335˙069.00|
More than half of the persons with spinal cord injuries (SCI) are suffering from impairments of both hands, which results in a tremendous decrease of quality of life (QoL) and represents a major barrier for inclusion in society. Functional restoration is possible with neuroprostheses based on functional electrical stimulation (FES). However, current systems are non-intelligent, non-intuitive open loop systems without sensory feedback. MoreGrasp aims at developing a multi-adaptive, multimodal user interface including brain-computer interfaces (BCIs) for intuitive control of a semi-autonomous motor and sensory grasp neuroprosthesis to support activities of daily living in individuals with SCI. With such a system a bilateral grasp restoration may become reality. The multimodal interfaces will be based on non-invasive BCIs for decoding of movements intentions with gel-less electrodes and wireless amplifiers. The neuroprosthesis will include FES electrode arrays and different sensors to allow for implementation of predefined or autonomously learned sequences. MoreGrasp will consequently follow the concept of the user-centered design by providing a scalable, modular, user-specific neuroprosthesis together with personalized EEG recording technology. Novel multimodal software architectures including interoperability standards will be defined to integrate neuroprostheses into the field of assistive technology. Long-term end user studies will demonstrate the reliability, usefulness and impact on QoL of the MoreGrasp technology. A web-based service infrastructure including a discussion forum will be set up for assessing user priorities and screening of users’ status. The evaluation of the training and patterns of use will allow for user modeling to identify factors for successful use. The highly interdisciplinary MoreGrasp consortium consists of members from universities, industry and rehabilitation centers, which have a long history of successful cooperation.
|Registration and Matchmaking Platform I||Demonstrators, pilots, prototypes||2019-05-31 12:28:34|
|Shared control evaluation||Documents, reports||2019-05-31 12:28:36|
|Registration and Matchmaking Platform II||Demonstrators, pilots, prototypes||2019-05-31 12:28:39|
|Review of sensors and integrated displays for the interactive environments||Documents, reports||2019-05-31 12:28:30|
Take a look to the deliverables list in detail: detailed list of MoreGrasp deliverables.
|year||authors and title||journal||last update|
Jane E. Huggins, Christoph Guger, Mounia Ziat, Thorsten O. Zander, Denise Taylor, Michael Tangermann, Aureli Soria-Frisch, John Simeral, Reinhold Scherer, RÃ¼diger Rupp, Giulio Ruffini, Douglas K. R. Robinson, Nick F. Ramsey, Anton Nijholt, Gernot MÃ¼ller-Putz, Dennis J. McFarland, Donatella Mattia, Brent J. Lance, Pieter-Jan Kindermans, IÃ±aki Iturrate, Christian Herff, Disha Gupta, An H. Do, Jennifer L. Collinger, Ricardo Chavarriaga, Steven M. Chase, Martin G. Bleichner, Aaron Batista, Charles W. Anderson, Erik J. Aarnoutse
Workshops of the Sixth International Brainâ€“Computer Interface Meeting: brainâ€“computer interfaces past, present, and future
published pages: 3-36, ISSN: 2326-263X, DOI: 10.1080/2326263X.2016.1275488
|Brain-Computer Interfaces 4/1-2||2019-05-29|
Stratified, computational interaction via machine learning
published pages: , ISSN: , DOI:
|The Eighteenth Yale Workshop on Adaptive and Learning Systems, Ed. K. Narendra, Yale, June 21-23rd, 2017||2019-05-29|
MÃ¼ller-Putz, G.R.; Ofner, P.; Schwarz, A.; Pereira, J.; Luzhnica, G.; di Sciascio, C.; Veas, E.; Stein, S.; Williamson, J.; Murray-Smith, R.; Escolano, C.; Montesano, L.; Hessing, B.; Schneiders, M.; Rupp, R.
Moregrasp: Restoration of Upper Limb Function in Individuals with High Spinal Cord Injury by Multimodal Neuroprostheses for Interaction in Daily Activities
published pages: , ISSN: , DOI: 10.3217/978-3-85125-533-1-62
Andreas Schwarz; Joana Pereira; Patrick Ofner; MÃ¼ller-Putz, Gernot R.
Movements of the same upper limb can be classified from low-frequency time-domain EEG signals
published pages: , ISSN: , DOI: 10.3217/978-3-85125-467-9-69
Patrick Ofner; Andreas Schwarz; Joana Pereira; MÃ¼ller-Putz, Gernot R.
Time domain classification of grasp and hold tasks
published pages: , ISSN: , DOI: 10.3217/978-3-85125-467-9-76
Patrick Ofner, Andreas Schwarz, Joana Pereira, Gernot R. MÃ¼ller-Putz
Upper limb movements can be decoded from the time-domain of low-frequency EEG
published pages: e0182578, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0182578
|PLOS ONE 12/8||2019-05-29|
Patrick Ofner; Andreas Schwarz; Joana Pereira; MÃ¼ller-Putz, Gernot R.
Discriminating goal-directed from nongoal-directed movements and its potential impact for BCI control
published pages: , ISSN: , DOI: 10.3217/978-3-85125-467-9-67
Joana Pereira, Patrick Ofner, Andreas Schwarz, Andreea Ioana Sburlea, Gernot R. MÃ¼ller-Putz
EEG neural correlates of goal-directed movement intention
published pages: 129-140, ISSN: 1053-8119, DOI: 10.1016/j.neuroimage.2017.01.030
Filip Melinscak, Luis Montesano
Beyond p-values in the evaluation of brainâ€“computer interfaces: A Bayesian estimation approach
published pages: 30-45, ISSN: 0165-0270, DOI: 10.1016/j.jneumeth.2016.06.008
|Journal of Neuroscience Methods 270||2019-05-29|
JÃ¶rg MÃ¼ller, Antti Oulasvirta, Roderick Murray-Smith
Control Theoretic Models of Pointing
published pages: 1-36, ISSN: 1073-0516, DOI: 10.1145/3121431
|ACM Transactions on Computer-Human Interaction 24/4||2019-05-29|
G.R. MÃ¼ller-Putz, A. Schwarz, J. Pereira, P. Ofner
From classic motor imagery to complex movement intention decoding: The noninvasive Graz-BCI approach
published pages: , ISSN: , DOI: 10.1016/bs.pbr.2016.04.017
|Progress in Brain Research||2019-05-29|
Maximilian Hommelsen, Matthias Schneiders, Christian Schuld, Philipp Keyl, RÃ¼diger Rupp
Sensory Feedback Interferes with Mu Rhythm Based Detection of Motor Commands from Electroencephalographic Signals
published pages: , ISSN: 1662-5161, DOI: 10.3389/fnhum.2017.00523
|Frontiers in Human Neuroscience 11||2019-05-29|
Karina Statthaler, Andreas Schwarz, David Steyrl, Reinmar Kobler, Maria Katharina HÃ¶ller, Julia Brandstetter, Lea Hehenberger, Marvin Bigga, Gernot MÃ¼ller-Putz
Cybathlon experiences of the Graz BCI racing team Mirage91 in the brain-computer interface discipline
published pages: , ISSN: 1743-0003, DOI: 10.1186/s12984-017-0344-9
|Journal of NeuroEngineering and Rehabilitation 14/1||2019-05-29|
Andrea KÃ¼bler, Gernot MÃ¼ller-Putz, Donatella Mattia
User-centred design in brainâ€“computer interface research and development
published pages: 312-314, ISSN: 1877-0657, DOI: 10.1016/j.rehab.2015.06.003
|Annals of Physical and Rehabilitation Medicine 58/5||2019-05-29|
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