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
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
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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Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.

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