Deans' stroke musings

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's quite disgusting that this information is not available from every stroke association and doctors group.
My back ground story is here:

Tuesday, March 14, 2017

Quantitative EEG for Predicting Upper-limb Motor Recovery in Chronic Stroke Robot-assisted Rehabilitation

Instead of doing these goddamn stupid recovery prediction models we should be researching exact recovery protocols. Do this, this and this and you have a 90% chance of recovering that function. THAT is what is needed, not this stupid lazy crap about recovery prediction.   Fugl-Meyer is totally useless in measurement of recovery, stop using it you fucking idiots.

Stroke is a leading cause for adult disability, which in many cases causes motor deficits. Despite the developments in motor rehabilitation techniques, recovery of upper limb functions after stroke is limited and heterogeneous in terms of outcomes, and knowledge of important factors that may affect the outcome of the therapy is necessary to make a reasonable prediction for individual patients. In this study, we assessed the relationship between quantitative electroencephalographic (QEEG) measures and the motor outcome in chronic stroke patients that underwent a robot-assisted rehabilitation program to evaluate the utility of QEEG indices to predict motor recovery. For this purpose, we acquired resting-state electroencephalographic signals from which the Power Ratio Index (PRI), Delta/Alpha Ratio (DAR), and Brain Symmetry Index (BSI) were calculated. The outcome of the motor rehabilitation was evaluated using upper-limb section of the Fugl-Meyer Assessment. We found that PRI was significantly correlated with the motor recovery, suggesting that this index may provide useful information to predict the rehabilitation outcome.

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