Euromov-DHM

Euromov Digital Health In Motion

Research Areas: Computer Science, Clinical Research, Science and Technology of Physical Activity and Sports

Director: Prof. Stéphane Perrey (University of Montpellier)
Co-director: Prof. Jacky Montmain (IMT Mines Alès)

The joint research unit (affiliated with the University of Montpellier and IMT Mines Alès)EuroMov Digital Health in Motion aimsto foster cross-fertilization between artificial intelligence, movement sciences, and health to understand human behavioral plasticity in order to improve sensorimotor performance and explore new therapeutic approaches, while also finding a scientific metaphor that serves as a source of inspiration for new digital approaches: machine learning or adaptive control of complex systems, human-machine interaction, and context-aware software systems. This research line on “Digital Health in Motion” ultimately aims to better understand the etiology of human movement—considered as the level of integration of biological and cognitive phenomena—during our ongoing informational exchanges with the environment.

The research unit comprises approximately 100 people: 43 faculty members, including 39 tenured faculty; 12 associate staff members (fixed-term contracts, tenured university hospital staff); 9 research support staff, including 4 IRs, 1 IE, and 3 BIATS; about 30 doctoral students; and Master’s students (research interns or engineering students).

The research unit is located at several sites: the EuroMov building (Veyrassi Campus, UFR STAPS, Montpellier), which also houses startups andseveral experimental and technological platforms, a building on the Louis Leprince Ringuet Technology Campus (IMT Mines Alès), and facilities dedicated to motion analysis for patients at the university hospitals in Nîmes (including the Grau-du-Roi site) and Montpellier, as well as at the Beausoleil Clinic (motion and sleep).

The unit is organized into three scientific themes and two cross-cutting areas:

  • Theme: Perception in Action & Synchronization (PIAS): exploring the laws governing human perception in moving agents (perception in action) and human-environment synchronization in general.
  • Theme: Monitoring and Improving Behaviors (MIB): Providing users with guidance on how to improve their behaviors in order to achieve better health, quality of life, or athletic performance, with a particular focus on software engineering.
  • Learning and Complexity (LAC) Theme: focuses on the study of human learning and complexity through the analysis of health-related movement patterns, clinical data, and neural activity indicators, with a particular emphasis on developing interpretable models.
  • Cross-cutting research area: Semantics and Taxonomy of Movement (SemTaxM): identifying taxonomic classifications of movement and defining a theory of movement-based semantics and semantic models grounded in specific contexts.
  • The TransversalAxisaimsto improve the reproducibility of results and accelerate translational research and technology transfer by providing standardized and documented approaches, along with an open data dissemination strategy.

Supervising institutions: University of Montpellier, IMT Mines Alès

Healthcare Partners: Montpellier University Hospital, Nîmes University Hospital, Beausoleil Clinic, and the Korian Group (R&D).

Academic Divisions: Biology and Health (BS); Mathematics, Computer Science, Physics, and Systems (MIPS)

Doctoral Programs: Human Movement Sciences (SMH); Information, Structures, and Systems (I2S)

Research areas:Biomechanics, Computer Science, Neuroscience, Physiology, Psychology, Neuroergonomics, Physical Medicine and Rehabilitation.Keywords:brain activity, physical activity, analysis, decision support, learning, cognition, data, fatigue, software engineering, imaging, interdisciplinarity, human-machine interface, Internet of Things, artificial intelligence, modeling, movement, digital, optimization, chronic conditions, perception, performance, plasticity, rhythms, health, sleep, sports, taxonomy, technologies, translational, computer vision