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.

Saturday, October 14, 2017

Markerless Human Motion Capture for Gait Analysis

Fuck this has been out since Oct. 2005. Our fucking failures of everything in stroke have had enough time to create objective analysis of gait disturbances and map stroke protocols to fix them. But NO, they are lazily waiting for SOMEONE ELSE TO SOLVE THE PROBLEM? 

Markerless Human Motion Capture for Gait Analysis

Jamal Saboune (INRIA Lorraine - LORIA), François Charpillet (INRIA Lorraine - LORIA)
The aim of our study is to detect balance disorders and a tendency towards the falls in the elderly, knowing gait parameters. In this paper we present a new tool for gait analysis based on markerless human motion capture, from camera feeds. The system introduced here, recovers the 3D positions of several key points of the human body while walking. Foreground segmentation, an articulated body model and particle filtering are basic elements of our approach. No dynamic model is used thus this system can be described as generic and simple to implement. A modified particle filtering algorithm, which we call Interval Particle Filtering, is used to reorganise and search through the model's configurations search space in a deterministic optimal way. This algorithm was able to perform human movement tracking with success. Results from the treatment of a single cam feeds are shown and compared to results obtained using a marker based human motion capture system.
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:cs/0510063 [cs.AI]
(or arXiv:cs/0510063v1 [cs.AI] for this version)

Submission history

From: Jamal Saboune [view email] [via CCSD proxy]
[v1] Fri, 21 Oct 2005 13:45:49 GMT (300kb)

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