Changing stroke rehab and research worldwide now.Time is Brain!Just think of all the trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 493 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:

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.
My back ground story is here:http://oc1dean.blogspot.com/2010/11/my-background-story_8.html

Monday, October 22, 2018

Upper Limb Recovery Prediction After Stroke Rehabilitation Based on Regression Method

Just why the fuck are you looking at recovery predictions? Rather than solving all the problems in stroke and writing stroke rehab protocols? Laziness? Incompetence? Or just don't care? No leadership? No strategy? Not my job?

 

Upper Limb Recovery Prediction After Stroke Rehabilitation Based on Regression Method

 

  • Ghada M. Bani Musa
  • Fady Alnajjar
  • Adel Al-Jumaily
  • Shingo Shimoda
  • Ghada M. Bani Musa
    • 1
  • Fady Alnajjar
    • 2
    • 3
  • Adel Al-Jumaily
    • 1
  • Shingo Shimoda
    • 3
  1. 1.Faculty of Engineering and Information TechnologyUniversity of Technology SydneySydneyAustralia
  2. 2.College of Information Technology (CIT)United Arab Emirates UniversityAl AinUAE
  3. 3.Intelligent Behavior Control UnitRikenWakoJapan
Conference paper
Part of the Biosystems & Biorobotics book series (BIOSYSROB, volume 21)

Abstract

In this paper, we investigate the possibility of a machine-learning algorithm using the Support Victor Machine Regression (SVMR) to predict the motor functional recovery of moderate post stroke patients during their rehabilitation program. To train the model, we used the recorded electromyography (EMG) signals from the upper limb muscles of the patients during their initial rehabilitation sessions. Then we tested the trained model to predict the later muscles performance of the patient during the same sessions. The results of this pilot study were promising; data were, to some extent, predictable. We believe such research direction could be essential to motivate the patient to complete the designed rehabilitation program and can assist the therapist to innovate proper rehabilitation menu for individual patients.

Keywords

Upper limb Rehabilitation Regression SVMR 

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