Éditeur(s) :
HAL CCSD Résumé : International audience
The development of predictive tools has been commonly utilized as the most effective manner to prevent illnesses thatstrike suddenly. Within this context, investigations linking fine human motor control with brain stroke risk factors areconsidered to have a high potential but they are still in an early stage of research. The present paper analysesneuromuscular features of oscillatory movements based on the Omega-Lognormal model of the Kinematic Theory. On adatabase of oscillatory movements from 120 subjects, we demonstrate that the proposed features differ significantlybetween subjects with and without brain stroke risk factors. This promising result motivates the development ofpredictive tools based on the Omega-Lognormal model.
17th Biennial Conference of the International Graphonomics Society
Pointe-à-Pitre, Guadeloupe
hal-01165773
https://hal.univ-antilles.fr/hal-01165773 https://hal.univ-antilles.fr/hal-01165773/document https://hal.univ-antilles.fr/hal-01165773/file/IGS_2015_submission_9.pdf