Laurent Navarro

Université Claude Bernard Lyon 1

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PÉ

Pascal Édouard

Centre Hospitalier Universitaire de Saint-Étienne

Stéphane Avril

Université Jean Monnet

Jérôme Molimard

Biologie, Ingénierie et Imagerie de la Greffe de Cornée

Guy Courbebaisse

Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé

Karsten Hollander

MSH Medical School Hamburg – University of Applied Sciences and Medical University

Pierre‐Eddy Dandrieux

Université Jean Monnet

Baptiste Pierrat

Mines Saint-Étienne

Astrid Junge

MSH Medical School Hamburg – University of Applied Sciences and Medical University

Pedro Branco

World Anti-Doping Agency

Jeanne Tondut

Laboratoire Interuniversitaire de Biologie de la Motricité

Cooperative Institutions

Université Claude Bernard Lyon 1

Centre National de la Recherche Scientifique

Inserm

Université Jean Monnet

Mines Saint-Étienne

Biologie, Ingénierie et Imagerie de la Greffe de Cornée

Centre Hospitalier Universitaire de Saint-Étienne

Sorbonne Université

Université Grenoble Alpes

Laboratoire Interuniversitaire de Biologie de la Motricité

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Physics-Informed Graph Neural Networks to solve 1-D equations of blood flow

Computer Methods and Programs in Biomedicine (2024)

Ahmet Şen Elnaz Ghajar-Rahimi Miquel Aguirre Laurent Navarro Craig J. Goergen

Control flow graph

10.1016/j.cmpb.2024.108427

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Effect of an unsupervised multidomain intervention integrating education, exercises, psychological techniques and machine learning feedback, on injury risk reduction in athletics (track and field): protocol of a randomised controlled trial (I-ReductAI)

BMJ Open Sport & Exercise Medicine (2025)

Spyridon Iatropoulos Pierre‐Eddy Dandrieux David Blanco Alexis Ruffault Estelle Gignoux

The primary aim is to assess the impact of a multidomain intervention that integrates education, exercise, psychological techniques and machine learning feedback on the duration athletes remain free from injury complaints leading to participation restriction (ICPR) during a 20-week summer competitive athletics season. The secondary aims are to assess the intervention's effect on reducing (i) the incidence, (ii) the burden, (iii) the period prevalence and (iv) the weekly prevalence of ICPR during the same timeframe. We will perform a two-arm randomised controlled trial. This study will involve an intervention group and a control group of competitive athletes licensed with the French Federation of Athletics, aged between 18 and 45, over an outdoor athletics competitive season lasting 20 weeks (March to July 2025). Data will be collected before the start (demographic, training and injury history) and one time per day (training and competition volume/intensity, perceived physical and psychological state, and illness and injury incidents) for both groups. The intervention group will be required to (i) view a series of 12 educational videos on injury prevention, (ii) engage in discipline-specific exercise programmes, (iii) implement stress and anxiety management techniques and (iv) view daily the injury prognostic feedback generated by the athlete's collected data based on machine learning. Outcomes will be analysed over the final 14 weeks of follow-up to allow time for the intervention to establish any potential efficacy. The primary outcome will be the time-to-event for each ICPR. Secondary outcomes will include (i) incidence, (ii) burden, (iii) period prevalence and (iv) weekly prevalence of ICPR. The primary outcome will be analysed using a Prentice-Williams-Peterson gap-time model. In contrast, the secondary outcomes will employ Poisson (i, ii), logistic (iii) and generalised estimating equations (iv) regression models, respectively.

Field trial

10.1136/bmjsem-2025-002501

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Three-dimensional representation of the phase of a signal in a time-frequency plan - Contribution to the analysis of quasi-stationary signals.

HAL (Le Centre pour la Communication Scientifique Directe) (2007)

Laurent Navarro

Representation

SIGNAL (programming language)

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Lattice Boltzmann Method for Heterogeneous Multi-Class Traffic Flow

Journal of Computational and Theoretical Transport (2020)

Romain Noël Laurent Navarro Guy Courbebaisse

Traffic modeling often keeps the mesoscopic scale in the theoretical sphere because of the integro-differential nature of its equations. In the present work, it is suggested to use the lattice Boltzmann method to overcome these difficulties while benefiting the strong theoretical foundation of the method. An alternative version of the lattice Boltzmann method for multi-class and heterogeneity in traffic flow is elaborated in this paper. Its ability to reproduce the fundamental diagram is proved, for both single-class and multi-class flows. This allows easily simulating complex and realistic cases of mixture of multi-class traffic flow. These simulations are able to capture jamming in various traffic situations such as road merging, reduction of the number of lanes or change of speed limits.

Lattice Boltzmann methods

Mesoscopic physics

Lattice (music)

10.1080/23324309.2020.1828468

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Citations (6)

Volume Rendering and Lattice-Boltzmann Method

HAL (Le Centre pour la Communication Scientifique Directe) (2017)

Fei Ge Romain Noël Laurent Navarro Guy Courbebaisse

Lattice Boltzmann methods

Source

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High Risk Of Heat-related Illnesses For Endurance Athletes During Athletics Championships In Hot Climate

Medicine & Science in Sports & Exercise (2021)

Karsten Hollander Milan Klöwer Andrew D. Richardson Laurent Navarro Sébastien Racinais

PURPOSE: To analyze the relationship between climatic conditions and the occurrence of heat-related illnesses during international athletics championships. METHODS: In this population-based study, all heat-related illnesses were selected from prospectively collected illness data from seven international outdoor World and European athletics championships between 2009 and 2018. The Universal Thermal Climate Index (UTCI) of each championship day was calculated as a model of thermoregulation for climatic conditions. The incidence rates of heat-related illnesses were analyzed in relation to the daily maximum UTCI temperature by fitting linear models. In addition, the relative risk (RR) was calculated for athletes from endurance and explosive disciplines, and for women and men. RESULTS: Overall, 132 heat-related illnesses occurred during the 50 championship days with UTCI temperatures between 15° and 37°Celsius (C). The average incidence rate of heat-related illness was 11.7 (95%CI 9.7 to 13.7) per 1000 registered athletes. The expected daily incidence rate of heat-related illness increased significantly with UTCI temperature (0.14 more illnesses per 1000 registered athletes per °C; 95%CI 0.10 to 0.18), doubling from 25 to 35 °C UTCI. No severe heat illness was observed below a UTCI temperature of 28 °C. Athletes in endurance disciplines had higher incidence rates than in explosive disciplines (RR = 21.7, 95% CI 12.0 to 39.2), while female and male athletes did not differ. CONCLUSION: More heat-related illness occurred on championship days with higher UTCI temperatures. There was a 20-fold increased risk in endurance disciplines compared with explosive disciplines. Strategies to prevent heat-related illness should focus on endurance disciplines in athletics competitions that occur in warm and humid climates with UTCI above 28 °C.

Heat illness

10.1249/01.mss.0000761444.67818.62

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Lattice Boltzmann Method & Mathematical Morphology

HAL (Le Centre pour la Communication Scientifique Directe) (2019)

Romain Noël Laurent Navarro Guy Courbebaisse

This paper suggests to build a direct link between the mathematical morphology and the Lattice Boltzmann Method (LBM) which leads to the LB3M (Lattice Boltzmann Method & Mathematical Morphology). To do so, a proof of the equivalence between the equations in the method and the definitions of morphological dilation and erosion in grey level is established. Thanks to the LB3M, the image processing and the physical simulation are embedded in the same formalism. In order to illustrate the efficiency of the suggested method, the elementary operations are applied to the Lena's image, then an example of bone growth is studied.

Lattice Boltzmann methods

Dilation (metric space)

Lattice (music)

Lattice gas automaton

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In vivo Identification of the Passive Mechanical Properties of Deep Soft Tissues in the Human Leg

Strain (2016)

Fanny Frauziols Fanette Chassagne Pierre Badel Laurent Navarro Jérôme Molimard

Abstract A non‐invasive method is proposed to identify in vivo the passive mechanical properties of deep soft tissues in the human leg. Force‐displacement curves in response to a localized compression of the calf are measured with a custom made experimental set‐up. The material parameters of a finite element model are then calibrated against the experimental curves using a genetic algorithm. A thorough investigation of the efficacy of this method to identify such mechanical properties is conducted through a design of experiments analysis and mixed numerical–experimental validations. It is the first time that a thorough analysis is conducted to really separate the contribution of deep and superficial tissues in the response to compression tests, and this permits to estimate the parameters of deep soft tissues on four subjects independently of the response of their other tissues. Two strain energy density functions are compared. It is shown that a 2nd order‐reduced polynomial better describes the passive mechanical behavior of the deep soft tissues of the leg than the neo‐Hookean model.

Strain (injury)

10.1111/str.12204

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Prediction of the Biomechanical Effects of Compression Therapy by Finite Element Modeling and Ultrasound Elastography

IEEE Transactions on Biomedical Engineering (2014)

Fanny Frauziols Jérôme Molimard Laurent Navarro Pierre Badel Magalie Viallon

In the present study, the biomechanical response of soft tissues from the fascia cruris to the skin is studied in the human leg under elastic compression.The distribution of elastic moduli in these tissues is measured for a volunteer at inactive and active muscle states using transient ultrasound elastography (TUSE). After registering the elasticity maps against magnetic resonance imaging scans of the same volunteer, patient-specific finite element (FE) models are developed for the leg cross section at inactive and active muscle states. Elastic properties obtained with TUSE are assigned at each Gauss point of the models. The response to 20 mmHg elastic compression is eventually predicted with the models.Results show significantly higher elastic moduli in the fascia cruris tissue and also a significant increase of elastic moduli at active muscle state.This seems to have a marginal impact on pressure maps in the soft tissues of the leg predicted by the FE models. There is still an effect on the reduction of vein diameter induced by elastic compression, which is decreased at active muscle state.The discussion of this paper highlights the benefits of using elastography to reconstruct patient-specific FE models of soft tissues.

Magnetic Resonance Elastography

Elasticity

10.1109/tbme.2014.2378553

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Citations (20)

Time-scale joint representation of DNS and LES numerical data

Computers & Fluids (2010)

Guy Courbebaisse Roland Bouffanais Laurent Navarro Emmanuel Leriche Michel Deville

Large-Eddy Simulation

Representation

10.1016/j.compfluid.2010.09.004

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Citations (2)