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Motor Imagery for Severely Motor-Impaired Patients: Evidence for Brain-Computer Interfacing as Superior Control Solution

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-119331
  • 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 shortBrain-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.zeige mehrzeige weniger

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Metadaten
Autor(en): Johannes Höhne, Elisa Holz, Pit Staiger-Sälzer, Klaus-Robert Müller, Andrea Kübler, Michael Tangermann
URN:urn:nbn:de:bvb:20-opus-119331
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Fakultät für Humanwissenschaften (Philos., Psycho., Erziehungs- u. Gesell.-Wissensch.) / Institut für Psychologie
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):PLoS ONE
Erscheinungsjahr:2014
Band / Jahrgang:9
Heft / Ausgabe:8
Seitenangabe:e104854
Originalveröffentlichung / Quelle:PLoS ONE 9(8): e104854. doi:10.1371/journal.pone.0104854
DOI:https://doi.org/10.1371/journal.pone.0104854
PubMed-ID:https://pubmed.ncbi.nlm.nih.gov/25162231
Allgemeine fachliche Zuordnung (DDC-Klassifikation):1 Philosophie und Psychologie / 15 Psychologie / 150 Psychologie
Freie Schlagwort(e):electroencephalography; eyes; games; hands; machine learning; man-computer interface; signal filtering; social communication
Datum der Freischaltung:21.10.2015
EU-Projektnummer / Contract (GA) number:224631
EU-Projektnummer / Contract (GA) number:216886
EU-Projektnummer / Contract (GA) number:216886
OpenAIRE:OpenAIRE
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung