EEG classifier cross-task transfer to avoid training sessions in robot-assisted rehabilitation

arXiv:2402.17790v1 Announce Type: cross
Abstract: Background: For an individualized support of patients during rehabilitation, learning of individual machine learning models from the human electroencephalogram (EEG) is required. Our approach allows labeled training data to be recorded without the need for a specific training session. For this, the planned exoskeleton-assisted rehabilitation enables bilateral mirror therapy, in which movement intentions can be inferred from the activity of the unaffected arm. During this therapy, labeled EEG data can be collected to enable movement …

abstract arxiv classifier cs.lg data eeg eess.sp human machine machine learning machine learning models patients robot session support training training data transfer type