Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setup
Abstract Invasive brain–computer-interfaces (BCIs) aim to improve severely paralyzed patient’s (e.g. tetraplegics) quality of life by using decoded movement intentions to let them interact with robotic limbs. We argue that the performance in controlling an end-effector using a BCI depends on three m...
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2021-02-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-021-84288-5 |
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doaj-858aa7999574496386f4518f46d6bed52021-03-11T12:10:56ZengNature Publishing GroupScientific Reports2045-23222021-02-0111111410.1038/s41598-021-84288-5Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setupRobin Lienkämper0Susanne Dyck1Muhammad Saif-ur-Rehman2Marita Metzler3Omair Ali4Christian Klaes5Department of Neurosurgery, University Hospital Knappschaftskrankenhaus Bochum GmbH, Ruhr-University BochumDepartment of Neurosurgery, University Hospital Knappschaftskrankenhaus Bochum GmbH, Ruhr-University BochumDepartment of Neurosurgery, University Hospital Knappschaftskrankenhaus Bochum GmbH, Ruhr-University BochumDepartment of Neurosurgery, University Hospital Knappschaftskrankenhaus Bochum GmbH, Ruhr-University BochumDepartment of Neurosurgery, University Hospital Knappschaftskrankenhaus Bochum GmbH, Ruhr-University BochumDepartment of Neurosurgery, University Hospital Knappschaftskrankenhaus Bochum GmbH, Ruhr-University BochumAbstract Invasive brain–computer-interfaces (BCIs) aim to improve severely paralyzed patient’s (e.g. tetraplegics) quality of life by using decoded movement intentions to let them interact with robotic limbs. We argue that the performance in controlling an end-effector using a BCI depends on three major factors: decoding error, missing somatosensory feedback and alignment error caused by translation and/or rotation of the end-effector relative to the real or perceived body. Using a virtual reality (VR) model of an ideal BCI decoder with healthy participants, we found that a significant performance loss might be attributed solely to the alignment error. We used a shape-drawing task to investigate and quantify the effects of robot arm misalignment on motor performance independent from the other error sources. We found that a 90° rotation of the robot arm relative to the participant leads to the worst performance, while we did not find a significant difference between a 45° rotation and no rotation. Additionally, we compared a group of subjects with indirect haptic feedback with a group without indirect haptic feedback to investigate the feedback-error. In the group without feedback, we found a significant difference in performance only when no rotation was applied to the robot arm, supporting that a form of haptic feedback is another important factor to be considered in BCI control.https://doi.org/10.1038/s41598-021-84288-5 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Robin Lienkämper Susanne Dyck Muhammad Saif-ur-Rehman Marita Metzler Omair Ali Christian Klaes |
spellingShingle |
Robin Lienkämper Susanne Dyck Muhammad Saif-ur-Rehman Marita Metzler Omair Ali Christian Klaes Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setup Scientific Reports |
author_facet |
Robin Lienkämper Susanne Dyck Muhammad Saif-ur-Rehman Marita Metzler Omair Ali Christian Klaes |
author_sort |
Robin Lienkämper |
title |
Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setup |
title_short |
Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setup |
title_full |
Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setup |
title_fullStr |
Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setup |
title_full_unstemmed |
Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setup |
title_sort |
quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setup |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2021-02-01 |
description |
Abstract Invasive brain–computer-interfaces (BCIs) aim to improve severely paralyzed patient’s (e.g. tetraplegics) quality of life by using decoded movement intentions to let them interact with robotic limbs. We argue that the performance in controlling an end-effector using a BCI depends on three major factors: decoding error, missing somatosensory feedback and alignment error caused by translation and/or rotation of the end-effector relative to the real or perceived body. Using a virtual reality (VR) model of an ideal BCI decoder with healthy participants, we found that a significant performance loss might be attributed solely to the alignment error. We used a shape-drawing task to investigate and quantify the effects of robot arm misalignment on motor performance independent from the other error sources. We found that a 90° rotation of the robot arm relative to the participant leads to the worst performance, while we did not find a significant difference between a 45° rotation and no rotation. Additionally, we compared a group of subjects with indirect haptic feedback with a group without indirect haptic feedback to investigate the feedback-error. In the group without feedback, we found a significant difference in performance only when no rotation was applied to the robot arm, supporting that a form of haptic feedback is another important factor to be considered in BCI control. |
url |
https://doi.org/10.1038/s41598-021-84288-5 |
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