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, May 29, 2011

Automatic identification of gait events using an instrumented sock

And maybe we could put estim in there also to prevent
inversion.
http://www.jneuroengrehab.com/content/8/1/32/
Abstract (provisional)
Background
Textile-based transducers are an emerging technology in
which piezo-resistive properties of materials are used to
measure an applied strain. By incorporating these sensors
into a sock, this technology offers the potential to detect
critical events during the stance phase of the gait cycle.
This could prove useful in several applications, such as
functional electrical stimulation (FES) systems to assist
gait.
Methods
We investigated the output of a knitted resistive strain
sensor during walking and sought to determine the degree of
similarity between the sensor output and the ankle angle in
the sagittal plane. In addition, we investigated whether it
would be possible to predict three key gait events, heel
strike, heel lift and toe off, with a relatively straight-
forward algorithm. This worked by predicting gait events to
occur at fixed time offsets from specific peaks in the
sensor signal.
Results
Our results showed that, for all subjects, the sensor output
exhibited the same general characteristics as the ankle
joint angle. However, there were large between-subjects
differences in the degree of similarity between the two
curves. Despite this variability, it was possible to
accurately predict gait events using a simple algorithm.
This algorithm displayed high levels of trial-to-trial
repeatability.
Conclusions
This study demonstrates the potential of using textile-based
transducers in future devices that provide active gait
assistance

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