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.

Friday, February 19, 2021

Robot-assisted rehabilitation of hand function after stroke: Development of prediction models for reference to therapy

Useless, the conclusion suggests planning specific therapies, BUT DOES NOTHING.

Robot-assisted rehabilitation of hand function after stroke: Development of prediction models for reference to therapy

Abstract

Background

Recovery of hand function after stroke represents the hardest target for clinicians. Robot-assisted therapy has been proved to be effective for hand recovery. Nevertheless, studies aimed to refer patients to the best therapy are missing.

Methods

With the aim to identify which clinical features are predictive for referring to robot-assisted hand therapy, 174 stroke patients were assessed with: Fugl-Meyer Assessment (FMA), Functional Independence Measure (FIM), Reaching Performance Scale (RPS), Box and Block Test (BBT), Modified Ashworth Scale (MAS), Nine Hole Pegboard Test (NHPT). Moreover, patients ability to control the robot with residual force and surface EMG (sEMG) independently, was checked. ROC curves were calculated to determine which of the measures were the predictors of the event.

Results

sEMG control (AUC = 0.925) was significantly determined by FMA upper extremity (FMUE) (>24/66) and sensation (>23/24) sections, MAS at Flexor Carpi (<3/4) and total MAS (>4/20). Force control (AUC = 0.928) was correlated only with FMUE (>24/66).

Conclusions

FMUE and MAS were the best predictors of preserved ability to control the device by two different modalities. This finding opens the possibility to plan specific therapies aimed at maximizing the highest functional outcome achievable after stroke.

 

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