Cross-domain prediction approach of human lower limb voluntary movement intention for exoskeleton robot based on EEG signals.

ABSTRACT:

Background and objective

Exoskeleton robot control should ideally be based on human voluntary movement intention. The readiness potential (RP) component of the motion-related cortical potential is observed before movement in the electroencephalogram and can be used for intention prediction. However, its single-trial features are weak and highly variable, and existing methods cannot achieve high cross-temporal and cross-subject accuracies in practical online applications. Therefore, this work aimed to combine a deep convolutional neural network (CNN) framework with a transfer learning (TL) strategy to predict the lower limb voluntary movement intention, thereby improving the accuracy while enhancing the model generalization capability; this would also provide sufficient processing t

SUBMITTER: Dong R 

PROVIDER: S-EPMC11377221 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature