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Monitoring Neuromotricity On-line: a Cloud Computing Approach

Abstract : The goal of our experiment is to develop a useful and accessible tool that can be used to evaluate a patient's health by analyzing handwritten strokes. We use a cloud computing approach to analyze stroke data sampled on a commercial tablet working on the Android platform and a distant server to perform complex calculations using the Delta and Sigma lognormal algorithms. A Google Drive account is used to store the data and to ease the development of the project. The communication between the tablet, the cloud and the server is encrypted to ensure biomedical information confidentiality. Highly parameterized biomedical tests are implemented on the tablet as well as a free drawing test to evaluate the validity of the data acquired by the first test compared to the second one. A blurred shape model descriptor pattern recognition algorithm is used to classify the data obtained by the free drawing test. The functions presented in this paper are still currently under development and other improvements are needed before launching the application in the public domain.
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Contributor : Philippe Simon <>
Submitted on : Saturday, June 20, 2015 - 4:47:52 PM
Last modification on : Monday, March 29, 2021 - 11:50:04 AM
Long-term archiving on: : Tuesday, September 15, 2015 - 7:57:40 PM


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  • HAL Id : hal-01165890, version 1



Olivier Lefebvre, Pau Riba, Jules Gagnon-Marchand, Charles Fournier, Alicia Fornes, et al.. Monitoring Neuromotricity On-line: a Cloud Computing Approach. 17th Biennial Conference of the International Graphonomics Society, International Graphonomics Society (IGS); Université des Antilles (UA), Jun 2015, Pointe-à-Pitre, Guadeloupe. ⟨hal-01165890⟩



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