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Journal Articles IEEE Transactions on Human-Machine Systems Year : 2022

On Computer Mouse Pointing Model Online Identification and Endpoint Prediction

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Abstract

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.
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Dates and versions

hal-03501383 , version 1 (23-12-2021)

Identifiers

  • HAL Id : hal-03501383 , version 1

Cite

Anatolii Khalin, Rosane Ushirobira, Denis Efimov, Géry Casiez. On Computer Mouse Pointing Model Online Identification and Endpoint Prediction. IEEE Transactions on Human-Machine Systems, 2022, 52 (5). ⟨hal-03501383⟩
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