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Structured dataset of human-machine interactions enabling adaptive user interfaces.

Angela Carrera-Rivera¹, Daniel Reguera-Bakhache², Felix Larrinaga²

¹Faculty of Engineering, Electronics, and Computing. Mondragon Unibertsitatea, Arrasate-Mondragon, 20500, Spain. aicarrera@mondragon.edu.

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Summary

This summary is machine-generated.

A new dataset captures human-machine interactions to aid adaptive Human-Machine Interface (HMI) development. This structured data offers insights into user behavior for interface design and analysis.

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Area of Science:

Computer Science
Human-Computer Interaction
Data Science

Background:

Human-Machine Interfaces (HMIs) are crucial for user interaction.
Developing adaptive HMIs requires comprehensive user behavior data.
Existing datasets may lack the structured detail needed for advanced HMI development.

Purpose of the Study:

Introduce a novel dataset of human-machine interactions.
Facilitate the development of adaptive Human-Machine Interfaces (HMIs).
Provide insights into user behavior for UI adaptation.

Main Methods:

Collected interaction data using a custom application with formally defined User Interfaces (UIs).
Processed and analyzed interaction data, including cleaning and ensuring consistency.
Conducted data profiling to verify interaction sequence consistency.

Main Results:

Generated a structured dataset of human-machine interactions.
The dataset is suitable for professionals and data analysts focused on UI adaptations.
Associated code for data collection and profiling is publicly available.

Conclusions:

The dataset provides a valuable resource for HMI research and development.
Availability of data and code supports advancements in adaptive user interfaces.
Enables deeper understanding and utilization of user interaction patterns.