A lower limb exoskeleton control system based on steady state visual evoked potentials

Objective. We have developed an asynchronous brain-machine interface (BMI)-based lower limb exoskeleton control system based on steady-state visual evoked potentials (SSVEPs). Approach. By decoding electroencephalography signals in real-time, users are able to walk forward, turn right, turn left, si...

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Bibliographic Details
Published inJournal of neural engineering Vol. 12; no. 5; pp. 56009 - 56022
Main Authors Kwak, No-Sang, Müller, Klaus-Robert, Lee, Seong-Whan
Format Journal Article
LanguageEnglish
Published England IOP Publishing 01.10.2015
Subjects
Adult
Artificial Limbs
Brain-Computer Interfaces
brain-machine interface
Classification
Control systems
electroencephalogram
Electroencephalography - instrumentation
Equipment Design
Equipment Failure Analysis
Evoked potentials
Evoked Potentials, Visual
exoskeleton control
Exoskeleton Device
Exoskeletons
Extraction
Feedback
Gait Disorders, Neurologic - physiopathology
Gait Disorders, Neurologic - rehabilitation
Humans
Limbs
Lower Extremity
Male
Robotics - instrumentation
steady state visual evoked potentials
Stimulation
Visual
Visual Perception
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Summary:Objective. We have developed an asynchronous brain-machine interface (BMI)-based lower limb exoskeleton control system based on steady-state visual evoked potentials (SSVEPs). Approach. By decoding electroencephalography signals in real-time, users are able to walk forward, turn right, turn left, sit, and stand while wearing the exoskeleton. SSVEP stimulation is implemented with a visual stimulation unit, consisting of five light emitting diodes fixed to the exoskeleton. A canonical correlation analysis (CCA) method for the extraction of frequency information associated with the SSVEP was used in combination with k-nearest neighbors. Main results. Overall, 11 healthy subjects participated in the experiment to evaluate performance. To achieve the best classification, CCA was first calibrated in an offline experiment. In the subsequent online experiment, our results exhibit accuracies of 91.3 5.73%, a response time of 3.28 1.82 s, an information transfer rate of 32.9 9.13 bits/min, and a completion time of 1100 154.92 s for the experimental parcour studied. Significance. The ability to achieve such high quality BMI control indicates that an SSVEP-based lower limb exoskeleton for gait assistance is becoming feasible.
Bibliography:ObjectType-Article-1
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ISSN:1741-2560
1741-2552
1741-2552
DOI:10.1088/1741-2560/12/5/056009