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:http://oc1dean.blogspot.com/2010/11/my-background-story_8.html

Thursday, January 19, 2017

Computational walking model could help stroke patients achieve optimal recovery

That model better get them to 100% recovery. From these comments(best possible recovery) they are already declaring defeat in the walking task.  Get them the hell out of this industry if they are declaring defeat so easily. We obviously have NO LEADERSHIP in stroke at all. Yes these are BHAGs(Big Hairy Audacious Goals) but they are doable if you set out to solve them. I would tackle them all.  Damnable Ph.Ds and not willing to do anything difficult.
http://www.news-medical.net/news/20170111/Computational-walking-model-could-help-stroke-patients-achieve-optimal-recovery.aspx
After a stroke, patients typically have trouble walking and few are able to regain the gait they had before suffering a stroke. Researchers funded by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) have developed a computational walking model that could help guide patients to their best possible recovery after a stroke. Computational modeling uses computers to simulate and study the behavior of complex systems using mathematics, physics, and computer science. In this case, researchers are developing a computational modeling program that can construct a model of the patient from the patient's walking data collected on a treadmill and then predict how the patient will walk after different planned rehabilitation treatments. They hope that one day the model will be able to predict the best gait a patient can achieve after completing rehabilitation, as well as recommend the best rehabilitation approach to help the patient achieve an optimal recovery.
Currently, there is no way for a clinician to determine the most effective rehabilitation treatment prescription for a patient. Clinicians cannot always know which treatment approach to use, or how the approach should be implemented to maximize walking recovery. B.J. Fregly, Ph.D. and his team (Andrew Meyer, Ph.D., Carolynn Patten, PT., Ph.D., and Anil Rao, Ph.D.) at the University of Florida developed a computational modeling approach to help answer these questions. They tested the approach on a patient who had suffered a stroke.
The team first measured how the patient walked at his preferred speed on a treadmill. Using those measurements, they then constructed a neuromusculoskeletal computer model of the patient that was personalized to the patient's skeletal anatomy, foot contact pattern, muscle force generating ability, and neural control limitations. Fregly and his team found that the personalized model was able to predict accurately the patient's gait at a faster walking speed, even though no measurements at that speed were used for constructing the model.
"This modeling effort is an excellent example of how computer models can make predictions of complex processes and accelerate the integration of knowledge across multiple disciplines,"says Grace Peng, Ph.D., director of the NIBIB program in Mathematical Modeling, Simulation and Analysis.
Fregly and his team believe this advance is the first step toward the creation of personalized neurorehabilitation prescriptions, filling a critical gap in the current treatment planning process for stroke patients. Together with devices that would ensure the patient is exercising using the proper force and torque, personalized computational models could one day help maximize the recovery of patients who have suffered a stroke.
"Through additional NIH funding, we are embarking with collaborators at Emory University on our first project to predict optimal walking treatments for two individuals post-stroke," says Fregly. "We are excited to begin exploring whether model-based personalized treatment design can improve functional outcomes."
Source:
National Institute of Biomedical Imaging and Bioengineering

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