On Computer Mouse Pointing Model Online ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
On Computer Mouse Pointing Model Online Identification and Endpoint Prediction
Auteur(s) :
Khalin, Anatolii [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Ushirobira, Rosane [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Casiez, Géry [Auteur]
Université de Lille
Technology and knowledge for interaction [LOKI]
Institut universitaire de France [IUF]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Finite-time control and estimation for distributed systems [VALSE]
Ushirobira, Rosane [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Casiez, Géry [Auteur]
Université de Lille
Technology and knowledge for interaction [LOKI]
Institut universitaire de France [IUF]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Titre de la revue :
IEEE Transactions on Human-Machine Systems
Éditeur :
IEEE
Date de publication :
2022-10
ISSN :
2168-2291
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Automatique / Robotique
Résumé en anglais : [en]
This paper proposes a new simplified pointing model as a feedback-based dynamical system, including both human and computer sides of the process. It takes into account the commutation between the correction and ballistic ...
Lire la suite >This paper proposes a new simplified pointing model as a feedback-based dynamical system, including both human and computer sides of the process. It takes into account the commutation between the correction and ballistic phases in pointing tasks. We use the mouse position increment signal from noisy experimental data to achieve our main objectives: to estimate the model parameters online and predict the task endpoint. Some estimation tools and validation results, applying linear regression techniques on the experimental data are presented. We also compare with a similar prediction algorithm to show the potential of our algorithm's implementation.Lire moins >
Lire la suite >This paper proposes a new simplified pointing model as a feedback-based dynamical system, including both human and computer sides of the process. It takes into account the commutation between the correction and ballistic phases in pointing tasks. We use the mouse position increment signal from noisy experimental data to achieve our main objectives: to estimate the model parameters online and predict the task endpoint. Some estimation tools and validation results, applying linear regression techniques on the experimental data are presented. We also compare with a similar prediction algorithm to show the potential of our algorithm's implementation.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
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