Yoann Poulet

Mr. Yoann Poulet


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
21 December 2022 in Sensors
Verified
Journal Article
Open access
PDF file
YPYoann Poulet
Yoann Poulet
FBFlorian Brassart
Florian Brassart
ESEmeline Simonetti
Emeline Simonetti
HPHelene Pillet
Helene Pillet
AFArnaud Faupin
Arnaud Faupin
CSChristophe Sauret
Christophe Sauret
The analysis of intra-cycle velocity profile of manual wheelchair (MWC) users has been used to highlight the significant role of trunk inertia in propulsion biomechanics. Maximal wheelchair linear velocity has previously been observed to be reached after the release of the handrims both during sports activities and daily life propulsion. This paper provides a combined analysis of linear velocity and trunk kinematics in elite wheelchair racing athletes during straight-line propulsion at stabilized speeds. MWC and trunk kinematics of eight athletes (level: 7 elite, 1 intermediate; classification: T54 (5), T53 (2) and T52 (1)) were monitored during 400 m races using inertial measurement units. An average propulsion cycle was computed for each athlete. The main finding of this article is the difference in propulsion patterns among the athletes, exhibiting either 1, 2 or 3 peaks in their velocity profile. A second peak in velocity is usually assumed to be caused by the inertia of the trunk. However, the presence of a second velocity peak among more severely impaired athletes with little to no trunk motion can either be associated to the inertia of the athletes’ arms or to their propulsion technique.

19 October 2020 in Computer Methods in Biomechanics and Biomedical Engineering
Verified
Journal Article
Open access
YPYoann Poulet
Yoann Poulet
CEC. Eyssartier
C. Eyssartier
TMT. Marsan
T. Marsan
LVL. Valdes-Tamayo
L. Valdes-Tamayo
MRM. Robert
M. Robert
CSC. Sauret
C. Sauret

25 July 2024 in Preprints.org
Verified
Preprint
Open access
PDF file
MDMathieu Deves
Mathieu Deves
CSChristophe Sauret
Christophe Sauret
AIAlberca Ilona
Alberca Ilona
LHLorian Honnorat
Lorian Honnorat
YPYoann Poulet
Yoann Poulet
AFArnaud Faupin
Arnaud Faupin
Background: Monitoring the mobility of players during wheelchair sports is essential to support coaches in their understanding of the activity and in their training programming. However, the amount of information available from the monitoring tools, combined with a general approach to processing and a poor presentation of the data to the coaches, is not effective and remains unused. Thus, this study aimed to propose a simple and efficient algorithm for identifying locomotor tasks (static, forward/backward propulsion, pivot/tight/wide rotation) during wheelchair movements based on wheelchair kinematic data. Methods: A total of 36 wheelchair tennis and badminton players participated, completing at least one of three proposed tests: the star test, the figure-of-eight test, and the forward-backward test. Locomotor tasks were identified using a five steps procedure including data reduction, symbolic approximation and pattern logical search. Results: Using this method, 99% of locomotor tasks were properly identified for the star test, 95% for the figure-of-eight test and 100% for the forward-backward test. Conclusion: This method appears to be a valuable tool for a simple and clear identification and representation of locomotor tasks over extended periods of time. Future research should aim at applying this method to multiple wheelchair court sports matches or daily life declination.

18 October 2024 in Methods and Protocols
Verified
Journal Article
Open access
PDF file
MDMathieu Deves
Mathieu Deves
CSChristophe Sauret
Christophe Sauret
AIAlberca Ilona
Alberca Ilona
LHLorian Honnorat
Lorian Honnorat
YPYoann Poulet
Yoann Poulet
AFArnaud Faupin
Arnaud Faupin
Background: Monitoring player mobility in wheelchair sports is crucial for helping coaches understand activity dynamics and optimize training programs. However, the lack of data from monitoring tools, combined with a lack of standardized processing approaches and ineffective data presentation, limits their usability outside of research teams. To address these issues, this study aimed to propose a simple and efficient algorithm for identifying locomotor tasks (static, forward/backward propulsion, pivot/tight/wide rotation) during wheelchair movements, utilizing kinematic data from standard wheelchair mobility tests. Methods: Each participant’s wheelchair was equipped with inertial measurement units—two on the wheel axes and one on the frame. A total of 36 wheelchair tennis and badminton players completed at least one of three proposed tests: the star test, the figure-of-eight test, and the forward/backward test. Locomotor tasks were identified using a five-step procedure involving data reduction, symbolic approximation, and logical pattern searching. Results: This method successfully identified 99% of locomotor tasks for the star test, 95% for the figure-of-eight test, and 100% for the forward/backward test. Conclusion: The proposed method offers a valuable tool for the simple and clear identification and representation of locomotor tasks over extended periods. Future research should focus on applying this method to wheelchair court sports matches and daily life scenarios.