EEG and EMG Driven Post-stroke Rehabilitation: a Review

The problem is that there is NO effective rehabilitation training!  100% recovery is the only goal to measure for effectiveness.

The evidence is that therapy after stroke is a complete fucking failure; only 10% get to full recovery from it

You're not doing anything about stopping the 5 causes of the neuronal cascade of death in the first days. This has been known for over a decade since the Rockefeller University described it in 2009. Why don't you solve that goddamn problem? By solving that you would save billions of neurons making it much more likely that you can improve the atrocious 10% chance of getting fully recovered.

The latest here:

EEG and EMG Driven Post-stroke Rehabilitation: a Review

PDF

Haiyang Yang; Jiacheng Wan; Ying Jin; Xixia Yu; Yinfeng Fang

All Authors

---

Abstract

Authors

Keywords

Abstract:

Intelligent post-stroke rehabilitation has attracted great attention, since the high incidence rate of stroke with the aging of the population world-widely. It is well known that effective rehabilitation training(There is none! If you don't know that, get the hell out of stroke!) can help the rehabilitation of neuromuscular injuries. In recent decades, biological signal-based closed-loop rehabilitation has significantly progressed and attracted widespread attention in clinics and academia, achieving relatively promising results. These biological signals are mainly electromyographic (EMG) signal and Electroencephalographic (EEG) signal. Firstly, this paper briefly overviews how to use EMG and EEG to be involved in rehabilitation. Special attention is paid to the detailed changes in EMG signal, EEG signal, and brain rhythm after stroke. Regarding technology-based intervention in stroke rehabilitation including intention cognitive, function rehabilitation devices, gesture decoded, and motor imagery. Finally, the feasibility of state-of-the-art motor function rehabilitation with EEG and EMG signals is analyzed. Our results show that rehabilitation with EEG and EMG signals is relatively more favorable than a single signal. Though the challenges may be tough, new theories and technological approaches able to exploit the full potential of EEG and EMG.

Published in: IEEE Sensors Journal ( Early Access )

Page(s): 1 - 1

Date of Publication: 14 November 2022

ISSN Information:

DOI: 10.1109/JSEN.2022.3220930

Publisher