Towards non-invasive Brain-Computer Interfaces for hand/arm control in users with spinal cord injury

Gernot Müller-Putz; Joana Pereira; Patrick Ofner; Andreas Schwarz; Catarina Lopes-Dias; Reinmar Kobler; Lea Hehenberger; Andreas Pinegger; Andreea Ioana Sburlea

doi:10.1109/IWW-BCI.2018.8311498

Towards non-invasive Brain-Computer Interfaces for hand/arm control in users with spinal cord injury

Gernot Müller-Putz, Joana Pereira, Patrick Ofner, Andreas Schwarz, Catarina Lopes-Dias, Reinmar Kobler, Lea Hehenberger, Andreas Pinegger, Andreea Ioana Sburlea

Institute of Neural Engineering (7090)

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

Abstract

Spinal cord injury (SCI) can disrupt the communication pathways between the brain and the rest of the body, restricting the ability to perform volitional movements. Neuroprostheses or robotic arms can enable individuals with SCI to move independently, improving their quality of life. The control of restorative or assistive devices is facilitated by brain-computer interfaces (BCIs), which convert brain activity into control commands. In this paper, we summarize the recent findings of our research towards the main aim to provide reliable and intuitive control. We propose a framework that encompasses the detection of goal-directed movement intention, movement classification and decoding, error-related potentials detection and delivery of kinesthetic feedback. Finally, we discuss future directions that could be promising to translate the proposed framework to individuals with SCI.

Original language	English
Title of host publication	2018 6th International Conference on Brain-Computer Interface (BCI)
Pages	65-68
Number of pages	4
ISBN (Electronic)	978-1-5386-2574-3
DOIs	https://doi.org/10.1109/IWW-BCI.2018.8311498
Publication status	Published - 15 Jan 2018
Event	6th International Winter Conference on Brain-Computer Interfaces: BCI 2018 - High1 Resort, Korea, Republic of Duration: 15 Jan 2018 → 17 Jan 2018

Conference

Conference	6th International Winter Conference on Brain-Computer Interfaces
Abbreviated title	BCI 2018
Country/Territory	Korea, Republic of
Period	15/01/18 → 17/01/18

Keywords

brain-computer interface
EEG
spinal cord injury
movement decoding
intuitive control

Fields of Expertise

Human- & Biotechnology

Access to Document

10.1109/IWW-BCI.2018.8311498

mueller_putz_winter_bci_conference_2018Final published version, 301 KBLicence: CC BY 4.0

EU - Feel Your Reach - Non-invasive decoding of cortical patterns induced by goal directed movement intentions and artificial sensory feedback in humans
Müller-Putz, G.
1/05/16 → 31/07/21
Project: Research project
MoreGrasp - Restoration of upper limb function in individuals with high spinal cord injury by multimodal neuroprostheses for interaction in daily activities
Müller-Putz, G.
1/03/15 → 31/05/18
Project: Research project

Cite this

Müller-Putz, G, Pereira, J, Ofner, P, Schwarz, A, Lopes-Dias, C, Kobler, R, Hehenberger, L, Pinegger, A & Sburlea, AI 2018, Towards non-invasive Brain-Computer Interfaces for hand/arm control in users with spinal cord injury. in 2018 6th International Conference on Brain-Computer Interface (BCI). pp. 65-68, 6th International Winter Conference on Brain-Computer Interfaces, Korea, Republic of, 15/01/18. https://doi.org/10.1109/IWW-BCI.2018.8311498

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abstract = "Spinal cord injury (SCI) can disrupt the communication pathways between the brain and the rest of the body, restricting the ability to perform volitional movements. Neuroprostheses or robotic arms can enable individuals with SCI to move independently, improving their quality of life. The control of restorative or assistive devices is facilitated by brain-computer interfaces (BCIs), which convert brain activity into control commands. In this paper, we summarize the recent findings of our research towards the main aim to provide reliable and intuitive control. We propose a framework that encompasses the detection of goal-directed movement intention, movement classification and decoding, error-related potentials detection and delivery of kinesthetic feedback. Finally, we discuss future directions that could be promising to translate the proposed framework to individuals with SCI.",

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author = "Gernot M{\"u}ller-Putz and Joana Pereira and Patrick Ofner and Andreas Schwarz and Catarina Lopes-Dias and Reinmar Kobler and Lea Hehenberger and Andreas Pinegger and Sburlea, {Andreea Ioana}",

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AU - Müller-Putz, Gernot

AU - Pereira, Joana

AU - Ofner, Patrick

AU - Schwarz, Andreas

AU - Lopes-Dias, Catarina

AU - Kobler, Reinmar

AU - Hehenberger, Lea

AU - Pinegger, Andreas

AU - Sburlea, Andreea Ioana

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AB - Spinal cord injury (SCI) can disrupt the communication pathways between the brain and the rest of the body, restricting the ability to perform volitional movements. Neuroprostheses or robotic arms can enable individuals with SCI to move independently, improving their quality of life. The control of restorative or assistive devices is facilitated by brain-computer interfaces (BCIs), which convert brain activity into control commands. In this paper, we summarize the recent findings of our research towards the main aim to provide reliable and intuitive control. We propose a framework that encompasses the detection of goal-directed movement intention, movement classification and decoding, error-related potentials detection and delivery of kinesthetic feedback. Finally, we discuss future directions that could be promising to translate the proposed framework to individuals with SCI.

KW - brain-computer interface

KW - EEG

KW - spinal cord injury

KW - movement decoding

KW - intuitive control

U2 - 10.1109/IWW-BCI.2018.8311498

DO - 10.1109/IWW-BCI.2018.8311498

M3 - Conference paper

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Y2 - 15 January 2018 through 17 January 2018

ER -

Towards non-invasive Brain-Computer Interfaces for hand/arm control in users with spinal cord injury

Abstract

Conference

Keywords

Fields of Expertise

Access to Document

Fingerprint

Projects

EU - Feel Your Reach - Non-invasive decoding of cortical patterns induced by goal directed movement intentions and artificial sensory feedback in humans

MoreGrasp - Restoration of upper limb function in individuals with high spinal cord injury by multimodal neuroprostheses for interaction in daily activities

Cite this