Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons

Edgar Jeevan Danaraj

doi:doi:10.11648/j.ijsspe.20261103.12

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Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons

Edgar Jeevan Danaraj^*

Published in International Journal of Sports Science and Physical Education (Volume 11, Issue 3)

Received: 6 October 2026 Accepted: 15 October 2026 Published: 28 October 2026

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Abstract

This study has two distinct components. First, an empirical secondary analysis applies a quadratic wind-normalization model to 20 recorded Southeast Asian (SEA) men's 100-m performances for which official times and wind readings were available in the compiled dataset. The mean official time was 10.399 ± 0.177 s and the mean model-adjusted time was 10.379 ± 0.185 s. The adjustment changes the relative ordering of some performances, illustrating how wind conditions can affect historical comparisons. Second, the paper presents a conceptual framework for an AI-powered lower-limb exoskeleton using inertial sensing, temporal-convolutional and recurrent neural-network components, athlete-specific digital twins, phase-specific assistance, and independent safety supervision. No exoskeleton intervention or athlete trial was conducted in this study; therefore, its proposed effects on sprint kinematics, performance, neuromuscular function, and injury risk remain hypotheses requiring controlled validation. The combined contribution is a wind-adjusted regional performance analysis and a technology proposal motivated by the training and performance questions that such comparisons raise.

Published in	International Journal of Sports Science and Physical Education (Volume 11, Issue 3)
DOI	10.11648/j.ijsspe.20261103.12
Page(s)	55-63
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

100-m Sprint, Southeast Asian Sprinting, Wind Normalization, Sprint Biomechanics, Resisted Sprint Training, Assisted Sprint Training, Artificial Intelligence, Wearable Robotics

References

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[2]	Mureika, Jonas. (2000). A realistic quasi-physical model of the 100 m dash. Canadian Journal of Physics. 79. 10.1139/cjp-79-4-697. https://doi.org/10.1139/cjp-79-4-697
[3]	Bartosz-Jeffries, M., Loturco, I., Zając, A., Maszczyk, A., Freitas, T. T., Alcaraz, P. E., Pereira, L. A., & Gołaś, A. (2025). Neuromuscular and Performance Responses to Resisted Sprint Loads in Elite Female Sprinters. Sports, 13(9), 327. https://doi.org/10.3390/sports13090327
[4]	Loturco I, Freitas TT, Zabaloy S, Pereira LA, Moura TBMA, Fernandes V, Mercer VP, Alcaraz PE, Zając A, Bishop C. Speed Training Practices of Brazilian Olympic Sprint and Jump Coaches: Toward a Deeper Understanding of Their Choices and Insights (Part II). J Hum Kinet. 2023 Oct 27; 89: 187-211. https://doi.org/10.5114/jhk/174071
[5]	Rodríguez-Fernández, A., Lobo-Prat, J. & Font-Llagunes, J. M. Systematic review on wearable lower-limb exoskeletons for gait training in neuromuscular impairments. J NeuroEngineering Rehabil 18, 22 (2021). https://doi.org/10.1186/s12984-021-00815-5
[6]	Bernuz B, Laujac S, Sirial C, Auffret S, Preda C, Slawinski J, Millot B, Pradon D, Coudrat L, Gavarry O. Effect of Advanced Footwear Technology Spikes on Sprint Acceleration: A Multiple N-of-1 Trial. Sports Med Open. 2024 Aug 30; 10(1): 92. https://doi.org/10.1186/s40798-024-00758-w
[7]	Mureika, J. R. (2000). A realistic quasi-physical model of the 100 metre dash (arXiv: physics/0007042). arXiv. https://arxiv.org/pdf/physics/0007042
[8]	Wind Correction Calculator: 100 m, 200 m, Long Jump - Track & Field AI, https://www.trackandfieldapp.com/wind-correction-calculator/
[9]	Cross, Matt & Lahti, Johan & Brown, Scott & Chedati, el & Jimenez-Reyes, Pedro & Samozino, Pierre & Eriksrud, Ola & Morin, Jean-Benoît. (2018). Training at maximal power in resisted sprinting: Optimal load determination methodology and pilot results in team sport athletes. PLOS ONE. 13. e0195477. https://doi.org/10.1371/journal.pone.0195477
[10]	Xu, K., Jukic, I., Cross, M. R., Hicks, D. S., Yin, M., Zhong, Y., Tang, W., Li, Y., Liang, Z., Wang, R., Morin, J.-B., & Girard, O. (2025). Effects of resisted-sprint training on sprint performance and mechanics: A systematic review and meta-analysis focusing on load magnitude. Scandinavian Journal of Medicine & Science in Sports, 35(12), e70182. https://doi.org/10.1111/sms.70182
[11]	Myrvang S, van den Tillaar R. The Longitudinal Effects of Resisted and Assisted Sprint Training on Sprint Kinematics, Acceleration, and Maximum Velocity: A Systematic Review and Meta-analysis. Sports Med Open. 2024 Oct 11; 10(1): 110. https://doi.org/10.1186/s40798-024-00777-7
[12]	Zhou, T., Zhou, Z., Zhang, H., & Chen, W. (2022). Modulating Multiarticular Energy during Human Walking and Running with an Unpowered Exoskeleton. Sensors, 22(21), 8539. https://doi.org/10.3390/s22218539

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APA Style

Danaraj, E. J. (2026). Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons. International Journal of Sports Science and Physical Education, 11(3), 55-63. https://doi.org/10.11648/j.ijsspe.20261103.12

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ACS Style

Danaraj, E. J. Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons. Int. J. Sports Sci. Phys. Educ. 2026, 11(3), 55-63. doi: 10.11648/j.ijsspe.20261103.12

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AMA Style

Danaraj EJ. Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons. Int J Sports Sci Phys Educ. 2026;11(3):55-63. doi: 10.11648/j.ijsspe.20261103.12

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@article{10.11648/j.ijsspe.20261103.12,
  author = {Edgar Jeevan Danaraj},
  title = {Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons},
  journal = {International Journal of Sports Science and Physical Education},
  volume = {11},
  number = {3},
  pages = {55-63},
  doi = {10.11648/j.ijsspe.20261103.12},
  url = {https://doi.org/10.11648/j.ijsspe.20261103.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsspe.20261103.12},
  abstract = {This study has two distinct components. First, an empirical secondary analysis applies a quadratic wind-normalization model to 20 recorded Southeast Asian (SEA) men's 100-m performances for which official times and wind readings were available in the compiled dataset. The mean official time was 10.399 ± 0.177 s and the mean model-adjusted time was 10.379 ± 0.185 s. The adjustment changes the relative ordering of some performances, illustrating how wind conditions can affect historical comparisons. Second, the paper presents a conceptual framework for an AI-powered lower-limb exoskeleton using inertial sensing, temporal-convolutional and recurrent neural-network components, athlete-specific digital twins, phase-specific assistance, and independent safety supervision. No exoskeleton intervention or athlete trial was conducted in this study; therefore, its proposed effects on sprint kinematics, performance, neuromuscular function, and injury risk remain hypotheses requiring controlled validation. The combined contribution is a wind-adjusted regional performance analysis and a technology proposal motivated by the training and performance questions that such comparisons raise.},
 year = {2026}
}

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TY  - JOUR
T1  - Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons
AU  - Edgar Jeevan Danaraj
Y1  - 2026/10/28
PY  - 2026
N1  - https://doi.org/10.11648/j.ijsspe.20261103.12
DO  - 10.11648/j.ijsspe.20261103.12
T2  - International Journal of Sports Science and Physical Education
JF  - International Journal of Sports Science and Physical Education
JO  - International Journal of Sports Science and Physical Education
SP  - 55
EP  - 63
PB  - Science Publishing Group
SN  - 2575-1611
UR  - https://doi.org/10.11648/j.ijsspe.20261103.12
AB  - This study has two distinct components. First, an empirical secondary analysis applies a quadratic wind-normalization model to 20 recorded Southeast Asian (SEA) men's 100-m performances for which official times and wind readings were available in the compiled dataset. The mean official time was 10.399 ± 0.177 s and the mean model-adjusted time was 10.379 ± 0.185 s. The adjustment changes the relative ordering of some performances, illustrating how wind conditions can affect historical comparisons. Second, the paper presents a conceptual framework for an AI-powered lower-limb exoskeleton using inertial sensing, temporal-convolutional and recurrent neural-network components, athlete-specific digital twins, phase-specific assistance, and independent safety supervision. No exoskeleton intervention or athlete trial was conducted in this study; therefore, its proposed effects on sprint kinematics, performance, neuromuscular function, and injury risk remain hypotheses requiring controlled validation. The combined contribution is a wind-adjusted regional performance analysis and a technology proposal motivated by the training and performance questions that such comparisons raise.
VL  - 11
IS  - 3
ER  -

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Author Information

Edgar Jeevan Danaraj

College of Engineering, Nanyang Technological University, Singapore

Contact Email

http://orcid.org/0000-0002-7785-7462

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Plain Text BibTeX RIS

APA Style

Danaraj, E. J. (2026). Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons. International Journal of Sports Science and Physical Education, 11(3), 55-63. https://doi.org/10.11648/j.ijsspe.20261103.12

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ACS Style

Danaraj, E. J. Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons. Int. J. Sports Sci. Phys. Educ. 2026, 11(3), 55-63. doi: 10.11648/j.ijsspe.20261103.12

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AMA Style

Danaraj EJ. Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons. Int J Sports Sci Phys Educ. 2026;11(3):55-63. doi: 10.11648/j.ijsspe.20261103.12

Copy | Download

@article{10.11648/j.ijsspe.20261103.12,
  author = {Edgar Jeevan Danaraj},
  title = {Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons},
  journal = {International Journal of Sports Science and Physical Education},
  volume = {11},
  number = {3},
  pages = {55-63},
  doi = {10.11648/j.ijsspe.20261103.12},
  url = {https://doi.org/10.11648/j.ijsspe.20261103.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsspe.20261103.12},
  abstract = {This study has two distinct components. First, an empirical secondary analysis applies a quadratic wind-normalization model to 20 recorded Southeast Asian (SEA) men's 100-m performances for which official times and wind readings were available in the compiled dataset. The mean official time was 10.399 ± 0.177 s and the mean model-adjusted time was 10.379 ± 0.185 s. The adjustment changes the relative ordering of some performances, illustrating how wind conditions can affect historical comparisons. Second, the paper presents a conceptual framework for an AI-powered lower-limb exoskeleton using inertial sensing, temporal-convolutional and recurrent neural-network components, athlete-specific digital twins, phase-specific assistance, and independent safety supervision. No exoskeleton intervention or athlete trial was conducted in this study; therefore, its proposed effects on sprint kinematics, performance, neuromuscular function, and injury risk remain hypotheses requiring controlled validation. The combined contribution is a wind-adjusted regional performance analysis and a technology proposal motivated by the training and performance questions that such comparisons raise.},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - Wind-Normalized Southeast Asian 100-m Sprint Performances and a Conceptual Framework for AI-Powered Exoskeletons
AU  - Edgar Jeevan Danaraj
Y1  - 2026/10/28
PY  - 2026
N1  - https://doi.org/10.11648/j.ijsspe.20261103.12
DO  - 10.11648/j.ijsspe.20261103.12
T2  - International Journal of Sports Science and Physical Education
JF  - International Journal of Sports Science and Physical Education
JO  - International Journal of Sports Science and Physical Education
SP  - 55
EP  - 63
PB  - Science Publishing Group
SN  - 2575-1611
UR  - https://doi.org/10.11648/j.ijsspe.20261103.12
AB  - This study has two distinct components. First, an empirical secondary analysis applies a quadratic wind-normalization model to 20 recorded Southeast Asian (SEA) men's 100-m performances for which official times and wind readings were available in the compiled dataset. The mean official time was 10.399 ± 0.177 s and the mean model-adjusted time was 10.379 ± 0.185 s. The adjustment changes the relative ordering of some performances, illustrating how wind conditions can affect historical comparisons. Second, the paper presents a conceptual framework for an AI-powered lower-limb exoskeleton using inertial sensing, temporal-convolutional and recurrent neural-network components, athlete-specific digital twins, phase-specific assistance, and independent safety supervision. No exoskeleton intervention or athlete trial was conducted in this study; therefore, its proposed effects on sprint kinematics, performance, neuromuscular function, and injury risk remain hypotheses requiring controlled validation. The combined contribution is a wind-adjusted regional performance analysis and a technology proposal motivated by the training and performance questions that such comparisons raise.
VL  - 11
IS  - 3
ER  -

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