Klinische Neurophysiologie 2013; 44(04): 263-267
DOI: 10.1055/s-0033-1357209
Originalia
© Georg Thieme Verlag KG Stuttgart · New York

Gehirn-Maschine-Interfaces (Brain-Machine Interfaces, BMI) zur Rehabilitation von Schlaganfall

BMI-Training with Body-Internalized FES or Other Wireless and/or Portable Devices
N. Birbaumer
1   Institut für medizinische Psychologie und Verhaltensneurobiologie, Universität Tübingen Ospedale San Camillo, IRCSS, Venedig, Italien
,
S. Silvoni
1   Institut für medizinische Psychologie und Verhaltensneurobiologie, Universität Tübingen Ospedale San Camillo, IRCSS, Venedig, Italien
,
A. Ramos
1   Institut für medizinische Psychologie und Verhaltensneurobiologie, Universität Tübingen Ospedale San Camillo, IRCSS, Venedig, Italien
› Author Affiliations
Further Information

Publication History

Publication Date:
19 December 2013 (online)

Zusammenfassung

BMI übersetzt Hirnsignale in Signale für körper-externe Maschinen und Computer ohne Beteiligung des motorischen Systems. BMIs wurden zur Rehabilitation von chronischem Schlaganfall meist in Kombination mit funktioneller Elek­trostimulation (FES), Robotern und Neuroprothesen und Physiotherapie benutzt. Zusätzlich zeigt Neurofeedback- und Biofeedbacktraining vielversprechende Ergebnisse als zusätzliche Rehabilitationsstrategie. Wenig gut kontrollierte klinische Studien mit hinreichend großen und homogenen Patientenstichproben stehen zur Verfügung, die meisten sind „proof-of-principle“ Versuche mit kleinen Stichproben. Die Kombination aus BMI-Neuroprothesen-Training mit Verhaltens-orientierter Physiotherapie hat sich als die wirksamste nicht-invasive Strategie bei schwerst gelähmten chronischen Schlaganfallpatienten erwiesen. In der Zukunft sollten invasive BMI-Trainings mit internalisierter FES und anderen drahtlosen und tragbaren Prothesen geprüft werden.

Abstract

BMI translates a brain signal to an external device without any motor involvement. BMIs have been used for rehabilitation of chronic stroke in combination with output devices such as functional electrical stimulation (FES), robots and exosceletons as a neuroprosthetic device, and physiotherapy. In addition, neurofeedback and biofeedback (usually using electromyographic (EMG) feedback) shows great promise as a rehabilitation strategy. However, very few adequately controlled studies with large enough patient samples are available, most report proof-of-principle strategies. The combination of BMI with behaviorally oriented physiotherapy to generalize BMI-treatment effects to the home environment proved to be the most efficient non-invasive rehabilitation strategy for severely paralyzed stroke victims. Future directions should test invasive.

 
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