Deans' stroke musings: Towards a robotic knee exoskeleton control based on human motion intention through EEG and sEMG signals

Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Sunday, November 29, 2020

Towards a robotic knee exoskeleton control based on human motion intention through EEG and sEMG signals

I looked but didn't find anything that suggested that my problem of knee snapping was addressed by any of these. I'm assuming that this is because my pre-motor cortex is mostly dead. My doctor explained absolutely nothing about why my deficits were occurring, he was completely useless.

Towards a robotic knee exoskeleton control based on human motion intention through EEG and sEMG signals

A.C.Villa-Parra a,b,

D.Delisle-Rodríguez a,c,

A. López-Delis c,

T. Bastos-Filho a,*,

R. Sagaró d,

A. Frizera-Neto a
a Post-Graduate Program in Electrical Engineering, Universidade Federal do Espírito Santo, Vitória,Brazil
b GIIB, Universidad Politécnica Salesiana, Cuenca, Ecuador
c Center of Medical Biophysics, Universidad de Oriente, Santiago,Cuba
d Mechanical and Design Engineering Department, Universidad de Oriente, Santiago,Cuba

Abstract

The integration of lower limb exoskeletons with robotic walkers allows obtaining a system to improve mobility and security duringgait rehabilitation. In this work, the evaluation of human motion intention (HMI) based on electroencephalogram (EEG) and surface electromyography (sEMG) signals are analyzed for a knee exoskeleton control as a preliminary study for gait neuro-rehabilitation with a hybrid robotic system. This system consists of the knee exoskeleton H2 and the UFES’s Smart Walker, which are used to restore the neuromotor control function of subjects with neural injuries. An experimental protocol was developed to identify patterns to control the exoskeleton in accordance with the HMI-based on EEG/sEMG. The EEG and sEMG signals are recorded during the following activities: stand-up/sit-down and knee flexion/extension. HMI is analyzed through both event-related desynchronization/synchronization (ERD/ERS) and slow cortical potential, as well as the myoelectric pattern classification related to lower limb. The feature extraction from sEMG signals is based on vector combinations in time and frequency domain which are used for a pattern classification stage trough an artificial neural network with Levenberg Marquadt training algorithm and support vector machine. Preliminary results shown that a combination of EEG/sEMG signals can be used to define a control strategy for the robotic system.©2015The Authors.Published by Elsevier