Financement de thèse – Nancy

Bonjour,

Vous trouverez ci-dessous un sujet de thèse interdisciplinaire IHM, STAPS et sciences cognitives.

Title: A multimodal study for modelling human motor performance and health in a Human – Robotics collaborative activity

Abstract:

New manufacturing concepts, such as “Biologicalisation in Manufacturing” that includes the digitalization of Human Factors, constitute a challenge of the next industry generations such as those promoted by “Industry of the Future”. In particular, the introduction of collaborative robotics – cobot (or collaborative devices) – in the service of human activity at work requires that humans and machines work together, which will transform work activities and would impact human motor behavior of workers, with potential consequences on health. However, no systemic approach was conducted to determine the effects of collaborative robotics introduction on performance and health in workers. The main scientific issue is to develop generic approach of experimental designs and multimodal measurements protocols with the aim to characterize different production situations. The underlying objective is to qualify predictors of worker’s health from the human-centered databases. The first exploratory study, based on two industrial reference situations (Use Cases), aims to contribute to analyze the biomechanical, behavioral and psychological factors of the motor performance and to identify new risks related to human-robot interaction. The second study aims at validating new multimodal models on an experimental laboratory platform that represents, as much as possible, the constraints and real needs of collaborative human-machine framework. The workflow consists of design of experiments, human measurements and data analyzing for making predictions relative to the health of workers.

Keywords (maximum 5): Human-machine interface; cobotics; biomechanics and psychological factors; human behavior modelling; performance and injuries and musculoskeletal disorders prevention.

Cette thèse sera dirigée par Gérome Gauchard  (EA 3450 DevAH « Development, Adaption and Disabilities », Axis 2: Exercise, Training, Performance) et co-dirigée par Sophie Lemonnier (EA 7312 PErSEUs « Ergonomics and Social Psychology for user exeprience »). Elle s’inscrit dans le projet C-SHIFT: Collaborative devices in the Service of Human activity at work in consistence with the challenges of Industry of the FuTure – HoW: Health of Workers. Ce projet débutera également en Septembre 2019 et est un consortium de six laboratoires de l’Université de Lorraine : LORIA, CRAN, CEREFIGE, PErSEUs, DevAH and LGIPM.

Pour candidater, veuillez envoyer un CV et une lettre de motivation aux deux adresses mails suivantes : gerome.gauchard@univ-lorraine.fr et sophie.lemonnier@univ-lorraine.fr , avant le 31 Mai. Vous pouvez également nous contacter si vous souhaitez plus d’information concernant le sujet de thèse et le projet dans lequel celui-ci s’inscrit.

 

Cordialement,

Sophie Lemonnier

Auteur du message
Lemonnier Sophie
E-mail
sophie.lemonnier@univ-lorraine.fr
Discipline scientifique
STAPS, IHM, Sciences cognitives
Lieu et institution de rattachement
Nancy, Université de Lorraine

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