Abstract
A new approach in motor rehabilitation after stroke is to use motor imagery (MI). To give feedback on MI performance brain–computer interface (BCIs) can be used. This requires a fast and easy acquisition of a reliable classifier. Usually, for training a classifier, electroencephalogram (EEG) data of MI without feedback is used, but it would be advantageous if we could give feedback right from the beginning. The sensorimotor EEG changes of the motor cortex during active and passive movement (PM) and MI are similar. The aim of this study is to explore, whether it is possible to use EEG data from active or PM to set up a classifier for the detection of MI in a group of elderly persons. In addition, the activation patterns of the motor cortical areas of elderly persons were analyzed during different motor tasks. EEG was recorded from three Laplacian channels over the sensorimotor cortex in a sample of 19 healthy elderly volunteers. Participants performed three different tasks in consecutive order, passive, active hand movement, and hand MI. Classifiers were calculated with data of every task. These classifiers were then used to detect event-related desynchronization (ERD) in the MI data. ERD values, related to the different tasks, were calculated and analyzed statistically. The performance of classifiers calculated from passive and active hand movement data did not differ significantly regarding the classification accuracy for detecting MI. The EEG patterns of the motor cortical areas during the different tasks was similar to the patterns normally found in younger persons but more widespread regarding localization and frequency range of the ERD. In this study, we have shown that it is possible to use classifiers calculated with data from passive and active hand movement to detect MI. Hence, for working with stroke patients, a physiotherapy session could be used to obtain data for classifier set up and the BCI-rehabilitation training could start immediately.
Highlights
According to the World Health Organization (WHO) 15 million people suffer a stroke every year, with one third of them left permanently disabled (Mackay and Mensah, 2004)
The event-related desynchronization (ERD)/event-related synchronization (ERS) pattern for the different motor tasks show ERD during movement or movement imagination, especially in a- and b-frequency bands, which turns to an ERS after termination of movement
ERD in the passive movement (PM) task seems to last some time after termination of movement before the ERS appears, whereas in the motor execution (ME) task ERS starts as soon as the movement stopped
Summary
According to the World Health Organization (WHO) 15 million people suffer a stroke every year, with one third of them left permanently disabled (Mackay and Mensah, 2004). Recovery of hand function is of importance for mastering activities of daily living but stroke rehabilitation is limited with 30 to 60% of patients being unable to use their more affected arm (Kwakkel et al, 1999). The preparation of a movement and MI are accompanied by a desynchronization of the m-rhythm (10–12 Hz) in the electroencephalogram (EEG) over motor cortical areas event-related desynchronization (ERD), especially in the hemisphere contralateral to the used arm (Pfurtscheller and Neuper, 1997). MI offers the opportunity to access the motor system at all stages of stroke recovery and induce activation of sensorimotor networks that were affected by lesions (Sharma et al, 2006). Up to now there are already some studies which reported a positive effect of MI on stroke rehabilitation outcome (Johnson-Frey, 2004; Gaggioli et al, 2005; Butler and Page, 2006; Page et al, 2007)
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