EEG-Based Asynchronous BCI Controls Functional Electrical Stimulation in a Tetraplegic Patient
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EEG-Based Asynchronous BCI Controls Functional Electrical Stimulation in a Tetraplegic Patient Gert Pfurtscheller Laboratory of Brain-Computer Interfaces, Institute of Computer Graphics and Vision, and Ludwig Boltzmann-Institute for Medical Informatics and Neuroinformatics, Graz University of Technology, Inffeldgasse 16a, 8010 Graz, Austria Email: [email protected]
¨ Gernot R. Muller-Putz Laboratory of Brain-Computer Interfaces, Institute of Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16a, 8010 Graz, Austria Email: [email protected]
¨ Pfurtscheller Jorg Department of Traumatology, Hospital Villach, Nikolaigasse 43, 9400 Villach, Austria Email: [email protected]
¨ Rudiger Rupp Department II, Orthopedic Hospital of Heidelberg University, Schlierbacher Landstraße 200a, 69118 Heidelberg, Germany Email: [email protected] Received 29 January 2004 The present study reports on the use of an EEG-based asynchronous (uncued, user-driven) brain-computer interface (BCI) for the control of functional electrical stimulation (FES). By the application of FES, noninvasive restoration of hand grasp function in a tetraplegic patient was achieved. The patient was able to induce bursts of beta oscillations by imagination of foot movement. These beta oscillations were recorded in a one EEG-channel configuration, bandpass filtered and squared. When this beta activity exceeded a predefined threshold, a trigger for the FES was generated. Whenever the trigger was detected, a subsequent switching of a grasp sequence composed of 4 phases occurred. The patient was able to grasp a glass with the paralyzed hand completely on his own without additional help or other technical aids. Keywords and phrases: beta oscillations, motor imagery, functional electrical stimulation, brain-computer interface, spinal cord injury, neuroprosthesis.
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INTRODUCTION
The idea of direct brain control of functional electrical stimulation (FES) seems to be a realistic concept for restoration of the hand grasp function in patients with a high spinal cord injury. Today, electrical brain activity either recorded from the intact scalp (EEG) or with subdural electrodes (ECoG) can be classified and transferred into signals for control of FES system (neuroprosthesis). Nowadays both implantable systems [1, 2] and devices using surface electrodes [3] are available for clinical use. For the transformation of mental commands reflected in changes of the brain signal into control signals for FES devices, an asynchronous, user-driven brain-computer interface (BCI) is necessary [4]. Such an asynchronous BCI analyses the EEG (ECoG) continuously and uses no cue stimuli.
For the realization of a reliable and easy to apply BCI, only one signal channel (one recording with two electrodes) should be used. Further, it is necessary to have a mental strategy established to produce short increases or bursts in the EEG (ECoG) amplitude and to detect the increase with a simple threshold comparator. We report for the first time
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