Factors that affect error potentials during a grasping task: toward a hybrid natural movement decoding BCI

Jason Omedes, Andreas Schwarz, Gernot R Müller-Putz, Luis Montesano

Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

Abstract

OBJECTIVE: This paper presents a hybrid BCI combining neural correlates of natural movements and interaction error-related potentials (ErrP) to perform a 3D reaching task. It focuses on the impact that design factors of such a hybrid BCI have on the ErrP signatures and in their classification.
 
 Approach. Users attempted to control a 3D virtual interface that simulated their own hand, to reach and grasp two different objects.
 Three factors of interest were modulated during the experimentation: (1) execution speed of the grasping, (2) type of grasping and (3) motor commands generated by motor imagery or real motion. Thirteen healthy subjects carried out the protocol. The peaks and latencies of the ErrP were analyzed for the different factors as well as the classification performance.
 
 Main results. ErrP are evoked for erroneous commands decoded from neural correlates of natural movements. The ANOVA analyses revealed that latency and magnitude of the most characteristic ErrP peaks were significantly influenced by the speed at which the grasping was executed, but not the type of grasp. This resulted in an greater accuracy of single-trial decoding of errors for fast movements (75.65%) compared to slow ones (68.99%). 
 
 Significance. Invariance of ErrP to different type of grasping movements and mental strategies proves this type of hybrid interface to be useful for the design of out of the lab applications such as the operation/control of prosthesis. Factors such as the speed of the movements have to be carefully tuned in order to optimize the performance of the system.&#13.

Originalspracheenglisch
Aufsatznummer046023
Seitenumfang15
FachzeitschriftJournal of neural engineering
Jahrgang15
Ausgabenummer4
DOIs
PublikationsstatusElektronische Veröffentlichung vor Drucklegung. - 1 Mai 2018

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Decoding
Imagery (Psychotherapy)
Hand Strength
Evoked Potentials
Prostheses and Implants
Analysis of Variance
Healthy Volunteers
Hand
Bioelectric potentials
Analysis of variance (ANOVA)
Invariance

Schlagwörter

    Fields of Expertise

    • Human- & Biotechnology

    Dies zitieren

    Factors that affect error potentials during a grasping task : toward a hybrid natural movement decoding BCI. / Omedes, Jason; Schwarz, Andreas; Müller-Putz, Gernot R; Montesano, Luis.

    in: Journal of neural engineering, Jahrgang 15, Nr. 4, 046023, 01.05.2018.

    Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

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