Young patients suffering from Cerebral Palsy are facing difficult choices concerning heavy surgeries. Diagnosis settled by surgeons can be complex and on the other hand decision for patient about getting or not such a surgery involves important reflection effort. Proposed software combining prediction for surgeries and post surgery kinematic values, and from 3D model representing the patient is an innovative tool helpful for both patients and medicine professionals. Beginning with analysis and classification of kinematics values from Data Base extracted from gait analysis in 3 separated clusters, it is possible to determine close similarity between patients. Prediction surgery best adapted to improve a patient gait is then determined by operating a suitable preconditioned neural network. Finally, patient 3D modeling based on kinematic values analysis, is animated thanks to post surgery kinematic vectors characterizing the closest patient selected from patients clustering.
A Predictive Rehabilitation Software for Cerebral Palsy Patients
2013-08-22
oai:zenodo.org:1086687
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC: | 629 |
British Library Conference Proceedings | 1992
|British Library Conference Proceedings | 1995
|Spasticity Effect in Cerebral Palsy Gait
Springer Verlag | 2018
|BASE | 2014
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