Detecting voluntary gait initiation/termination intention using EEG

In this study, we employed a linear classifier to grasp the abstract features of electroencephalography (EEG) for recognizing voluntary gait intention and termination. We monitored Mu-band EEG to find gait intention and tried to detect a movement on/offset. Considerable gait-related (de) synchronization occurred hence, amplified by common spatial pattern (CSP). Performance of the classifier was evaluated in terms of classification success rates and false positive rates.

[1]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[2]  Clemens Brunner,et al.  Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks , 2006, NeuroImage.

[3]  S. M. Morton,et al.  Cerebellar Control of Balance and Locomotion , 2004, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[4]  Alfred D. Grant Gait Analysis: Normal and Pathological Function , 2010 .

[5]  Dario Farina,et al.  Detection of movement-related cortical potentials based on subject-independent training , 2013, Medical & Biological Engineering & Computing.

[6]  Richard R Neptune,et al.  The effect of walking speed on muscle function and mechanical energetics. , 2008, Gait & posture.

[7]  G. Pfurtscheller,et al.  Optimal spatial filtering of single trial EEG during imagined hand movement. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[8]  J. Wolpaw,et al.  Mu and Beta Rhythm Topographies During Motor Imagery and Actual Movements , 2004, Brain Topography.

[9]  Jason B. Mattingley,et al.  Attention and the readiness for action , 2011, Neuropsychologia.

[10]  May Q. Liu,et al.  Muscle contributions to support and progression over a range of walking speeds. , 2008, Journal of biomechanics.