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, October 13, 2023

B-Spline Modeling of Inertial Measurements for Evaluating Stroke Rehabilitation Effectiveness

No clue.

 B-Spline Modeling of Inertial Measurements for Evaluating Stroke Rehabilitation Effectiveness

Yi-Ting Hwang, Yu-Qian Tung, Chun-Shu Chen, and Bor-Shing Lin, Senior Member, IEEE
Abstract— Patients who experience upper-limb paralysis
after stroke require continual rehabilitation. Rehabilitation
must be evaluated for appropriate treatment adjustment;
such evaluation can be performed using inertial measure-
ment units (IMUs) instead of standard scales or subjective
evaluations. However, IMUs produce large quantities of dis-
cretized data, and using these data directly is challenging.
In this study, B-splines were used to estimate IMU trajectory
data for objective evaluations of hand function and stability
by using machine learning classifiers and mathematical in-
dices. IMU trajectory data from a 2018 study on upper-limb
rehabilitation were used to validate the proposed method.
Features extracted from B-spline trajectories could be used
to classify individuals in the 2018 study with high accuracy,
and the proposed indices revealed differences between
these groups. Compared with conventional rehabilitation
evaluation methods, the proposed method is more objec-
tive and effective.

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