On Computer Mouse Pointing Model Online ...
Type de document :
Article dans une revue scientifique: Article original
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]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Institut universitaire de France [IUF]
Technology and knowledge for interaction [LOKI]
Université de Lille
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]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Institut universitaire de France [IUF]
Technology and knowledge for interaction [LOKI]
Université de Lille
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
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
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