A dataset and post-processing method for pointing device human-machine interface evaluation
The evaluation of human-machine interfaces (HMI) requires quantitative metrics to define the ability of a person to effectively achieve their goals using the HMI. In particular, for pointing-device type HMIs such as the computer mouse, an experiment quantifying movement by performing repetitive targ...
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| Autores principales: | , , |
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| Formato: | Articulo |
| Lenguaje: | Inglés |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/160151 |
| Aporte de: |
| Sumario: | The evaluation of human-machine interfaces (HMI) requires quantitative metrics to define the ability of a person to effectively achieve their goals using the HMI. In particular, for pointing-device type HMIs such as the computer mouse, an experiment quantifying movement by performing repetitive target selections allows defining a useful metric known as throughput (TP) using the Fitts' Law test. In this work, a dataset obtained from an automated protocol application is presented, which is made publicly available through an on-line platform. A post-processing method to obtain performance parameters from the dataset is also presented, and its output is used to validate the data against similar experiments in the literature. |
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