0000000000590927
AUTHOR
Arvind Tolambiya
showing 3 related works from this author
A classification study of kinematic gait trajectories in hip osteoarthritis
2014
The clinical evaluation of patients in hip osteoarthritis is often done using patient questionnaires. While this provides important information it is also necessary to continue developing objective measures. In this work we further investigate the studies concerning the use of 3D gait analysis to attain this goal. The gait analysis was associated with machine learning methods in order to provide a direct measure of patient control gait discrimination. The applied machine learning method was the support vector machine (SVM). Applying the SVM on all the measured kinematic trajectories, we were able to classify individual patient and control gait cycles with a mean success rate of 88%. With th…
''Modulation of Anticipatory Postural Activity For Multiple Conditions of A Whole-body Pointing Task''
2012
Tolambiya, A. | Chiovetto, E. | Pozzo, T. | Thomas, E.; International audience; ''This is a study on associated postural activities during the anticipatory segments of a multijoint movement. Several previous studies have shown that they are task dependant. The previous studies, however, have mostly been limited in demonstrating the presence of modulation for one task condition, that is, one aspect such as the distance of the target or the direction of reaching. Real-life activities like whole-body pointing, however, can vary in several ways. How specific is the adaptation of the postural activities for the diverse possibilities of a whole-body pointing task? We used a classification paradig…
An ensemble analysis of electromyographic activity during whole body pointing with the use of support vector machines.
2011
Import JabRef | WosArea Life Sciences and Biomedicine - Other Topics; International audience; We explored the use of support vector machines (SVM) in order to analyze the ensemble activities of 24 postural and focal muscles recorded during a whole body pointing task. Because of the large number of variables involved in motor control studies, such multivariate methods have much to offer over the standard univariate techniques that are currently employed in the field to detect modifications. The SVM was used to uncover the principle differences underlying several variations of the task. Five variants of the task were used. An unconstrained reaching, two constrained at the focal level and two …