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

Institut für Neurotechnologie (7090)

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband

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 inviduals with SCI.

Originalsprache	englisch
Titel	2018 6th International Conference on Brain-Computer Interface (BCI)
Seiten	65-68
Seitenumfang	4
ISBN (elektronisch)	978-1-5386-2574-3
DOIs	https://doi.org/10.1109/IWW-BCI.2018.8311498
Publikationsstatus	Veröffentlicht - 15 Jan. 2018
Veranstaltung	6th International Winter Conference on Brain-Computer Interfaces: BCI 2018 - High1 Resort, Südkorea Dauer: 15 Jan. 2018 → 17 Jan. 2018

Konferenz

Konferenz	6th International Winter Conference on Brain-Computer Interfaces
Kurztitel	BCI 2018
Land/Gebiet	Südkorea
Zeitraum	15/01/18 → 17/01/18

Fields of Expertise

Human- & Biotechnology

Zugriff auf Dokument

10.1109/IWW-BCI.2018.8311498

mueller_putz_winter_bci_conference_2018Endgültige, publizierte Fassung, 301 KBLizenz: CC BY 4.0

2 Abgeschlossen

EU - Feel Your Reach - Nichtinvasive Dekodierung von kortikalen Bewegungsvorstellungsmustern und künstliches Feedback im Menschen
Müller-Putz, G.
1/05/16 → 30/04/21
Projekt: Foschungsprojekt
MoreGrasp - Funktionswiederherstellung der oberen Extremität bei questschnittgelähmten Personen mit multimodalen Neuroprothesen für Aktivitäten des täglichen Lebens.
Müller-Putz, G.
1/03/15 → 31/05/18
Projekt: Foschungsprojekt

Dieses zitieren

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). S. 65-68, 6th International Winter Conference on Brain-Computer Interfaces, Südkorea, 15/01/18. https://doi.org/10.1109/IWW-BCI.2018.8311498

@inproceedings{12f52e9bf3b240dd9ac9a9c1ba558260,

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

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

keywords = "brain-computer interface, EEG, spinal cord injury, movement decoding, intuitive control",

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}",

year = "2018",

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doi = "10.1109/IWW-BCI.2018.8311498",

language = "English",

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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

PY - 2018/1/15

Y1 - 2018/1/15

N2 - Spinal cord injury (SCI) can disrupt thecommunication pathways between the brain and the rest of thebody, restricting the ability to perform volitional movements.Neuroprostheses or robotic arms can enable individuals with SCIto move independently, improving their quality of life. Thecontrol of restorative or assistive devices is facilitated by brain-computer interfaces (BCIs), which convert brain activity intocontrol commands.In this paper, we summarize the recent findings of our researchtowards the main aim to provide reliable and intuitive control.We propose a framework that encompasses the detection of goal-directed movement intention, movement classification anddecoding, error-related potentials detection and delivery ofkinesthetic feedback. Finally, we discuss future directions thatcould be promising to translate the proposed framework to inviduals with SCI.

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

SP - 65

EP - 68

BT - 2018 6th International Conference on Brain-Computer Interface (BCI)

T2 - 6th International Winter Conference on Brain-Computer Interfaces

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

Konferenz

Fields of Expertise

Zugriff auf Dokument

Fingerprint

Projekte

EU - Feel Your Reach - Nichtinvasive Dekodierung von kortikalen Bewegungsvorstellungsmustern und künstliches Feedback im Menschen

MoreGrasp - Funktionswiederherstellung der oberen Extremität bei questschnittgelähmten Personen mit multimodalen Neuroprothesen für Aktivitäten des täglichen Lebens.

Dieses zitieren