A new descriptor of neuroelectrical activity during BCI-assisted motor imagery-based training in stroke patients

M. Petti; D. Mattia; F. Pichiorri; J. Toppi; S. Salinari; F. Babiloni; L. Astolfi; F. Cincotti

doi:10.1109/EMBC.2014.6943828

A new descriptor of neuroelectrical activity during BCI-assisted motor imagery-based training in stroke patients

M. Petti, D. Mattia, F. Pichiorri, J. Toppi, S. Salinari, F. Babiloni, L. Astolfi, F. Cincotti

Fondazione Santa Lucia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In BCI applications for stroke rehabilitation, BCI systems are used with the aim of providing patients with an instrument that is capable of monitoring and reinforcing EEG patterns generated by motor imagery (MI). In this study we proposed an offline analysis on data acquired from stroke patients subjected to a BCI-assisted MI training in order to define an index for the evaluation of MI-BCI training session which is independent from the settings adopted for the online control and which is able to describe the properties of neuroelectrical activations across sessions. Results suggest that such index can be adopted to sort the trails within a session according to the adherence to the task.

Original language	English
Title of host publication	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1267-1269
Number of pages	3
ISBN (Print)	9781424479290
DOIs	https://doi.org/10.1109/EMBC.2014.6943828
Publication status	Published - Nov 2 2014
Event	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States Duration: Aug 26 2014 → Aug 30 2014

Other

Other	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Country/Territory	United States
City	Chicago
Period	8/26/14 → 8/30/14

ASJC Scopus subject areas

Health Informatics
Computer Science Applications
Biomedical Engineering

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10.1109/EMBC.2014.6943828

Cite this

Petti, M., Mattia, D., Pichiorri, F., Toppi, J., Salinari, S., Babiloni, F., Astolfi, L., & Cincotti, F. (2014). A new descriptor of neuroelectrical activity during BCI-assisted motor imagery-based training in stroke patients. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 (pp. 1267-1269). [6943828] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2014.6943828

A new descriptor of neuroelectrical activity during BCI-assisted motor imagery-based training in stroke patients. / Petti, M.; Mattia, D.; Pichiorri, F. et al.

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 1267-1269 6943828.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Petti, M, Mattia, D, Pichiorri, F, Toppi, J, Salinari, S, Babiloni, F, Astolfi, L & Cincotti, F 2014, A new descriptor of neuroelectrical activity during BCI-assisted motor imagery-based training in stroke patients. in 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014., 6943828, Institute of Electrical and Electronics Engineers Inc., pp. 1267-1269, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, Chicago, United States, 8/26/14. https://doi.org/10.1109/EMBC.2014.6943828

Petti M, Mattia D, Pichiorri F, Toppi J, Salinari S, Babiloni F et al. A new descriptor of neuroelectrical activity during BCI-assisted motor imagery-based training in stroke patients. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 1267-1269. 6943828 https://doi.org/10.1109/EMBC.2014.6943828

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AB - In BCI applications for stroke rehabilitation, BCI systems are used with the aim of providing patients with an instrument that is capable of monitoring and reinforcing EEG patterns generated by motor imagery (MI). In this study we proposed an offline analysis on data acquired from stroke patients subjected to a BCI-assisted MI training in order to define an index for the evaluation of MI-BCI training session which is independent from the settings adopted for the online control and which is able to describe the properties of neuroelectrical activations across sessions. Results suggest that such index can be adopted to sort the trails within a session according to the adherence to the task.

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A new descriptor of neuroelectrical activity during BCI-assisted motor imagery-based training in stroke patients

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