Human Factors Technologies

Smart assistants, self-driving cars, cognitive interfaces, automated decision support...

Labo bcom - technologies facteurs humains
© Fred Pieau
New technological challenges are leading us to fully rethink the relationship between humans and machines.

To enable true human-machine cooperation, the Human Factors Technologies lab analyzes and anticipates human behaviors in order to design smart environments that are effective, intuitive, and customized. By the same logic, it creates solutions founded on its expertise in psychophysiology, cognitive sciences, and interaction design. Using the best simulation and analysis methods, it develops user-centered interaction technologies and objective behavioral measurement tools to usher in the digital transformation of the industrial world and help create a new experience for its customers.

Guillaume Jegou - bcom

Guillaume Jegou

Human Factors Technologies lab Manager

At the intersection of Cognitive Science and Human Factors, we define innovations that ensure people are both the driver and end purpose of technological research.
products & services
interaction design for systems b<>com Ngagement

Une nouvelle génération d’outils XR, conçus pour minimiser les risques et optimiser la performance humaine de vos systèmes complexes.

scientific publications


A la recherche du temps perdu sur smartphone. L’impact des outils de monitoring sur la régulation des usages.

Les smartphones sont aujourd'hui massivement utilisés et posent des questions en termes de responsabilité numérique. En parallèle, les applications de suivi du temps d’utilisation sont devenues un sujet d'intérêt général. Cependant, peu d'études expérimentales étudient les effets réflexifs de ce contrôle (monitoring) sur les utilisateurs. Cet article présente ainsi une expérimentation…

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Une distraction librement consentie ? Usages du smartphone de jeunes étudiants

Les jeunes passent de plus en plus de temps sur leur smartphone et leur conscientisation de cet usage mérite d'être questionnée. Pour ce faire, nous avons interrogé des étudiants sur leur utilisation du smartphone. L'analyse des entretiens fait ressortir différents éléments : (1) les étudiants disent ressentir une culpabilité à passer trop de temps sur leur smartphone, souvent basée sur un…

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An Efficient Deep-Learning-Based Solution for the Recognition of Relative Changes in Mental Workload Using Wearable Sensors

In this work, a new solution for the automatic recognition of relative changes in mental workload is proposed. Wearable sensors were used to collect EEG, EDA, PPG and eyetracking data from 26 human subjects while performing the nback task with three difficulty levels n ∈ {1, 2, 3}. The objective is to recognize whether the mental workload is increasing, decreasing or stable by comparing the…

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Improving Collaborative Learning in Virtual Reality With Facial Expressions

This article presents an approach to improve collaborative learning in terms of performance &amp; satisfaction through the generation of non-verbal behavior of users displayed on their avatar in virtual reality. Various works have focused on the behavioral realism of avatars, which can considerably improve interactions. The purpose of this paper is to investigate the impact of displaying the…

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