Our Research
Scientific Positioning
The OxyMove Joint Research Laboratory develops advanced physiological monitoring solutions in dynamic conditions, with a central focus on the measurement and interpretation of muscle oxygenation in real-world settings.
The project is positioned at the intersection of movement sciences, exercise physiology, signal processing, and artificial intelligence. It aims to transform complex hemodynamic measurements into robust, scientifically validated indicators that can be effectively translated into actionable insights for athletes.
Muscle NIRS: Scientific Foundation of the Project
OxyMove’s research is grounded in functional near-infrared spectroscopy applied to skeletal muscle (muscle NIRS).
This non-invasive technology enables real-time measurement of:
Variations in muscle tissue oxygenation
Muscle oxygen saturation levels
Oxygenation and reoxygenation dynamics
Physiological adaptations to exercise and recovery
Muscle NIRS provides direct access to the mechanisms underlying oxygen utilization specifically at the muscular level.
A major objective of the project is to enhance the reliability of these measurements and to make them readily usable under dynamic conditions and in real-world environments.
Scientific Objectives
The OxyMove project pursues several key scientific objectives:
Characterization of Muscular Responses to Exercise
Investigate hemodynamic responses according to exercise modalities (endurance, strength, intermittent exercise), the muscle groups involved, and individual physiological profiles.
Identification of Physiological Biomarkers
Identify robust indicators of muscular load, fatigue, and recovery status.
Modeling of Individual Physiological Trajectories
Quantify inter-individual variability in physiological responses to exercise in order to develop personalized models tailored to performance and health objectives.
Development of Interpretative Algorithms
Design analytical methods integrating signal processing, artificial intelligence, and predictive modeling.
Research Axes and Methodology
Axis 1 – Sensor Development and Validation
Optimization of miniaturized, multi-channel muscle fNIRS sensors compatible with use under dynamic conditions.
Axis 2 – Signal Processing and Artificial Intelligence
Development of embedded algorithms enabling the extraction of robust physiological indicators.
Axis 3 – Experimental Protocols
Implementation of laboratory-based studies, controlled-environment experiments, and real-world investigations conducted in accordance with validated ethical standards.
Axis 4 – Data Structuring and Management
Establishment of multi-subject datasets enabling statistical analysis, modeling, and cross-validation of physiological indicators.
Scientific Roadmap
Scientific Implementation and Structuring
This initial phase focuses on structuring the Joint Research Laboratory and defining the methodological foundations of the project. It establishes the scientific, technical, and organizational framework necessary for the development of the research program.
Establish a multidisciplinary LabCom team
Install experimental setups and sensing systems
Define the initial scientific protocols
Structure the experimental strategy and use cases
Lay the methodological foundations of the project
Laboratory Exploration and Characterization
This phase is dedicated to the scientific exploration of muscular responses to exercise in controlled environments. It aims to improve the understanding of oxygenation dynamics and physiological mechanisms measured through mNIRS.
Characterize muscular hemodynamic responses
Analyze oxygenation and reoxygenation dynamics
Investigate factors influencing signal quality
Investigation Under Real-World Conditions
Experimental protocols are extended to dynamic and real-world contexts in order to examine physiological adaptations in sport-specific settings.
Compare laboratory and field-based responses
Analysis and Modeling
Collected data are processed using advanced signal processing and artificial intelligence methodologies.
Develop analytical algorithms
Identify robust physiological indicators
Model individual physiological trajectories
Structure tools for scientific interpretation
Optimization and Transfer
The final phase aims to consolidate scientific findings and integrate them into operational tools designed to address the needs of athletes.