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.

Thursday, November 21, 2019

A tactile sensing approach in stroke rehabilitation

You'll have to ask your doctor how this is going to get you recovered and how you will do enough repetitions in the therapy sessions to actually recover. 

A tactile sensing approach in stroke rehabilitation

Mikov, Nikolay; Mohagheghia, Amir; Kilbride, Cherry; Du, Xinli
Date: 2019

Abstract:

The paper describes an experimental, mechanically simple, tactile sensing solution in the form of a sensing chair for discriminating human motion in a reaching task. This cost-efficient technical approach was employed for the assessment of selective arm movements in stroke survivors. The sensing system classifies trunk motion in a seated stroke survivor during a goal-directed task where there is direct correlation with the level of severity of arm movement. The system interprets motion mechanically from coupled sensory data transients using artificial neural networks and shows tolerance to patients’ sitting posture and performance variability. The accuracy of classification was typically greater than 94% across three categories when applied to a group of stroke survivors of wide-ranging motor abilities. The mechanical simplicity, versatility of approach for use in other classes of movement, and potential low cost of manufacturing provides opportunity to employ the system at clinics and homes for assessment and training.

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