A Novel Nonlinear Dynamic Method for Stroke Rehabilitation Effect Evaluation using EEG

I can see nothing here that will help survivors get to 100% recovery.  Useless.
http://ieeexplore.ieee.org/abstract/document/8016662/?reload=true
Hong Zeng ; Guojun Dai ; Wanzeng Kong ; Fangyue Chen ; Luyun Wang

Abstract:

Evaluating the effect of stroke rehabilitation based on electroencephalogram (EEG) is still a challenging problem. This paper presents a novel nonlinear dynamic complexity method for the evaluation of stroke rehabilitation effect from EEG signal. Our method calculates the nonlinearly separable degree (NLSD) of EEG signal, and then employs an indicator, called Mean Nonlinearly Separable complexity Degree (Mean_NLSD), to efficiently and accurately evaluate therapy effect of stroke patients. Our study under twelve stimuli conditions on eleven patients and eleven control subjects indicates that in general Mean_NLSD is smaller at the lesion regions and that the Mean_NLSD of the control subjects is stochastic. Compared with conventional spectral methods such as mean Power Spectral Density (PSD), Mean_NLSD is more sensitive and robust. Overall Mean_NLSD may offer a promising approach to facilitate the evaluation of stroke rehabilitation effect.

Published in: IEEE Transactions on Neural Systems and Rehabilitation Engineering ( Volume: PP, Issue: 99 )

Page(s): 1 - 1

Date of Publication: 25 August 2017

ISSN Information:

DOI: 10.1109/TNSRE.2017.2744664

Publisher: IEEE

Sponsored by: IEEE Engineering in Medicine and Biology Society