Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.

Brain-Computer Interfaces (BCIs) strive to decode brain signals into control commands for severely handicapped people with no means of muscular control. These potential users of noninvasive BCIs display a large range of physical and mental conditions. Prior studies have shown the general applicabili...

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Autores principales: Johannes Höhne, Elisa Holz, Pit Staiger-Sälzer, Klaus-Robert Müller, Andrea Kübler, Michael Tangermann
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Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2014
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Acceso en línea:https://doaj.org/article/d01b9a6d62b24dc59058fc29d74d2783
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spelling oai:doaj.org-article:d01b9a6d62b24dc59058fc29d74d27832021-11-25T06:03:05ZMotor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.1932-620310.1371/journal.pone.0104854https://doaj.org/article/d01b9a6d62b24dc59058fc29d74d27832014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25162231/?tool=EBIhttps://doaj.org/toc/1932-6203Brain-Computer Interfaces (BCIs) strive to decode brain signals into control commands for severely handicapped people with no means of muscular control. These potential users of noninvasive BCIs display a large range of physical and mental conditions. Prior studies have shown the general applicability of BCI with patients, with the conflict of either using many training sessions or studying only moderately restricted patients. We present a BCI system designed to establish external control for severely motor-impaired patients within a very short time. Within only six experimental sessions, three out of four patients were able to gain significant control over the BCI, which was based on motor imagery or attempted execution. For the most affected patient, we found evidence that the BCI could outperform the best assistive technology (AT) of the patient in terms of control accuracy, reaction time and information transfer rate. We credit this success to the applied user-centered design approach and to a highly flexible technical setup. State-of-the art machine learning methods allowed the exploitation and combination of multiple relevant features contained in the EEG, which rapidly enabled the patients to gain substantial BCI control. Thus, we could show the feasibility of a flexible and tailorable BCI application in severely disabled users. This can be considered a significant success for two reasons: Firstly, the results were obtained within a short period of time, matching the tight clinical requirements. Secondly, the participating patients showed, compared to most other studies, very severe communication deficits. They were dependent on everyday use of AT and two patients were in a locked-in state. For the most affected patient a reliable communication was rarely possible with existing AT.Johannes HöhneElisa HolzPit Staiger-SälzerKlaus-Robert MüllerAndrea KüblerMichael TangermannPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 8, p e104854 (2014)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Johannes Höhne
Elisa Holz
Pit Staiger-Sälzer
Klaus-Robert Müller
Andrea Kübler
Michael Tangermann
Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.
description Brain-Computer Interfaces (BCIs) strive to decode brain signals into control commands for severely handicapped people with no means of muscular control. These potential users of noninvasive BCIs display a large range of physical and mental conditions. Prior studies have shown the general applicability of BCI with patients, with the conflict of either using many training sessions or studying only moderately restricted patients. We present a BCI system designed to establish external control for severely motor-impaired patients within a very short time. Within only six experimental sessions, three out of four patients were able to gain significant control over the BCI, which was based on motor imagery or attempted execution. For the most affected patient, we found evidence that the BCI could outperform the best assistive technology (AT) of the patient in terms of control accuracy, reaction time and information transfer rate. We credit this success to the applied user-centered design approach and to a highly flexible technical setup. State-of-the art machine learning methods allowed the exploitation and combination of multiple relevant features contained in the EEG, which rapidly enabled the patients to gain substantial BCI control. Thus, we could show the feasibility of a flexible and tailorable BCI application in severely disabled users. This can be considered a significant success for two reasons: Firstly, the results were obtained within a short period of time, matching the tight clinical requirements. Secondly, the participating patients showed, compared to most other studies, very severe communication deficits. They were dependent on everyday use of AT and two patients were in a locked-in state. For the most affected patient a reliable communication was rarely possible with existing AT.
format article
author Johannes Höhne
Elisa Holz
Pit Staiger-Sälzer
Klaus-Robert Müller
Andrea Kübler
Michael Tangermann
author_facet Johannes Höhne
Elisa Holz
Pit Staiger-Sälzer
Klaus-Robert Müller
Andrea Kübler
Michael Tangermann
author_sort Johannes Höhne
title Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.
title_short Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.
title_full Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.
title_fullStr Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.
title_full_unstemmed Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.
title_sort motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.
publisher Public Library of Science (PLoS)
publishDate 2014
url https://doaj.org/article/d01b9a6d62b24dc59058fc29d74d2783
work_keys_str_mv AT johanneshohne motorimageryforseverelymotorimpairedpatientsevidenceforbraincomputerinterfacingassuperiorcontrolsolution
AT elisaholz motorimageryforseverelymotorimpairedpatientsevidenceforbraincomputerinterfacingassuperiorcontrolsolution
AT pitstaigersalzer motorimageryforseverelymotorimpairedpatientsevidenceforbraincomputerinterfacingassuperiorcontrolsolution
AT klausrobertmuller motorimageryforseverelymotorimpairedpatientsevidenceforbraincomputerinterfacingassuperiorcontrolsolution
AT andreakubler motorimageryforseverelymotorimpairedpatientsevidenceforbraincomputerinterfacingassuperiorcontrolsolution
AT michaeltangermann motorimageryforseverelymotorimpairedpatientsevidenceforbraincomputerinterfacingassuperiorcontrolsolution
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