D5.1 Report on the methodology of Human factors countermeasures for HMI and UX for human and ML model Interaction (short version)

This is a short version of the report on the methodology of Human factors, countermeasures for HMI and UX for human and ML model Interaction. Here, the deliverable summarizes progress in enhancing Human-Machine Interaction in Air Traffic Control through user-centred AI design. Task 5.1 focuses on measuring human factors like stress and cognitive load using neurophysiological metrics (e.g., EEG, EDA) to inform adaptive system design. Task 5.2 develops Human-in-the-Loop frameworks using passive Brain-Computer Interfaces to improve AI transparency and responsiveness. The work supports trust, adaptability, and effective decision-making in AI-assisted ATC systems

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-24
DOI
https://doi.org/10.5281/zenodo.15728318
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

D5.1 Report on the methodology of Human factors countermeasures for HMI and UX for human and ML model Interaction (short version)

Zenodo (CERN European Organization for Nuclear Research)
Human-Automation Interaction and Safety
article

D5.1 Report on the methodology of Human factors countermeasures for HMI and UX for human and ML model Interaction (short version)

article en

Abstract

This is a short version of the report on the methodology of Human factors, countermeasures for HMI and UX for human and ML model Interaction. Here, the deliverable summarizes progress in enhancing Human-Machine Interaction in Air Traffic Control through user-centred AI design. Task 5.1 focuses on measuring human factors like stress and cognitive load using neurophysiological metrics (e.g., EEG, EDA) to inform adaptive system design. Task 5.2 develops Human-in-the-Loop frameworks using passive Brain-Computer Interfaces to improve AI transparency and responsiveness. The work supports trust, adaptability, and effective decision-making in AI-assisted ATC systems

Zenodo (CERN European Organization for Nuclear Research)
Mälardalen University (SE)
Peace, Justice and strong institutions
Openalex Percentile: Top 46%
Human-Automation Interaction and Safety
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