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document
Classification of motor imagery performance in acute stroke . OBJECTIVE Effective motor imagery performance , seen as strong suppression of the sensorimotor rhythm , is the key element in motor imagery therapy . Therefore , optimization of methods to classify whether the subject is performing the imagery task is a prerequisite . An optimal classification method should have high performance accuracy and use a small number of channels . We investigated the additional benefit of the common spatial pattern filtering ( CSP ) to a linear discriminant analysis ( LDA ) classifier , for different channel configurations . METHODS Ten hemispheric acute stroke patients and 11 healthy subjects were included . EEGs were recorded using 60 channels . The classifier was trained with a motor execution task . For both healthy controls and patients , analysis of recordings was initially limited to 3 and 11 electrodes recording from the motor cortex area , and later repeated using 45 electrodes . RESULTS No significant improvement on the addition of CSP to LDA was found ( in both cases , the area under the receiving operating characteristic ( AU-ROC ) ≈ 0.70 ( acceptable ) ) . We then repeated the LDA+CSP method on recordings of 45 electrodes , since the use of imagery neuronal circuits may well extend beyond the motor area . AU-ROC rose to 0.90 , but no virtual 'most responsible ' electrode was observed . Finally , in mild-to-moderate stroke patients we could successfully use the EEG data recorded from the healthy hemisphere to train the classifier ( AU-ROC ≈ 0.70 ) . SIGNIFICANCE Including only the channels on the unaffected motor cortex is sufficient to train a classifier .
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Intervention_Physical
motor imagery therapy .
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Intervention_Physical
EEGs
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Outcome_Other
motor imagery performance
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Outcome_Other
Effective motor imagery performance
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Outcome_Other
LDA
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Outcome_Other
area under the receiving operating characteristic ( AU-ROC )
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Outcome_Other
no virtual 'most responsible ' electrode
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Participant_Condition
acute stroke
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Participant_Sample-size
Ten
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Participant_Sample-size
11
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Participant_Condition
in mild-to-moderate stroke patients