Tecnologías emergentes aplicadas en el deporte1

Emerging technologies applied in sports.

El objetivo de este artículo es analizar la implementación de tecnologías
emergentes en el deporte para mejorar la experiencia de atletas,
entrenadores y aficionados. El mundo del deporte está en constante
innovación, lo que exige un manejo eficiente de herramientas tecnológicas
especializadas. Estas tecnologías emergentes se enfocan en ayudar a los
deportistas a rendir mejor en el campo de juego, optimizar los regímenes de
entrenamiento y revolucionar los procesos de toma de decisiones. Mediante
el uso de algoritmos de aprendizaje automático, análisis predictivos y
tecnologías de visión por computadora, se pueden establecer estrategias
efectivas. Para este estudio, se seleccionaron 40 artículos de bases de datos
como Scopus, ScienceDirect e IEEE. Los principales hallazgos indican que
las herramientas tecnológicas no solo mejoran la competitividad, sino que
también ayudan a prevenir lesiones futuras.

1. Adesida, Y., Papi, E., & McGregor, A. H. (2019). Exploring the role of wearable technology in sport kinematics and kinetics: A systematic review.
2. In Sensors (Switzerland) (Vol. 19, Issue 7). MDPI AG. https://doi.org/10.3390/s19071597
3. ALEXANDER, W. LINDSAY. (2019). ST. PAUL AT ATHENS (CLASSIC REPRINT). FORGOTTEN BOOKS. Apostolou, K., & Tjortjis, C. (2019, July 1). Sports
4. Analytics algorithms for performance prediction. 10th International Conference on Information, Intelligence, Systems and Applications, IISA 2019.
5. https://doi.org/10.1109/IISA.2019.8900754
6. Araújo, D., Couceiro, M., Seifert, L., Sarmento, H., & Davids, K. (2021). Artificial intelligence in sport performance analysis. In Artificial Intelligence in Sport Performance Analysis. Taylor and Francis. https://doi.org/10.4324/9781003163589
7. Biró, A., Cuesta-Vargas, A. I., & Szilágyi, L. (2024). AI-Assisted Fatigue and Stamina Control for Performance Sports on IMU-Generated Multivariate Times Series Datasets. Sensors, 24(1). https://doi.org/10.3390/s24010132
8. Calderón, R. (n.d.). Universidad La Salle Bienes comunes digitales de la Universidad La Salle Piedras angulares de la investigación forense sobre delitos
9. económicos Programa forense de delitos económicos !e Beneficios de la Inteligencia Arti&cial en Ciberseguridad.
10. Chen, G., & Wu, H. (2024). Optimization simulation of sports stadium training based on Ant colony algorithm and sensor network. Measurement:
11. Sensors, 33, 101100. https://doi.org/10.1016/j.measen.2024.101100
12. Chen, Z., & Dai, X. (2024). Utilizing AI and IoT technologies for identifying risk factors in sports. Heliyon, 10(11). https://doi.org/10.1016/j.heliyon.2024.e32477
13. Chidambaram, S., Maheswaran, Y., Patel, K., Sounderajah, V., Hashimoto, D. A., Seastedt, K. P., McGregor, A. H., Markar, S. R., & Darzi, A. (2022). Using
14. Artificial Intelligence-Enhanced Sensing and Wearable Technology in Sports Medicine and Performance Optimisation. In Sensors (Vol. 22, Issue 18). MDPI. https://doi.org/10.3390/s22186920
15. De Oliveira, M. S., Steffen, V., & Trojan, F. (2023). A systematic review of the literature on video assistant referees in soccer: Challenges and
16. opportunities in sports analytics. Decisión Analytics Journal, 7. https://doi.org/10.1016/j.dajour.2023.100232
17. Fuss, F. K. , S. A. , S. M. , & M. R. (2014). Routledge Handbook of Sports Technology and Engineering. Routledge.
18. Goel, A. (2024). IS TECHNOLOGY A COMPLEMENT OR SUBSTITUTE TO REFEREEING IN SPORTS? A REVIEW (Review study). IJSTS International Journal of Sport Technology
19. and Science International Journal of Sports Technology and Science, 2(1), 13–23. https://www.globsportsjournal.com/
20. Gsangaya, M. R., Htwe, O., Selvi Naicker, A., Md Yusoff, B. A. H., Mohammad, N., Soh, E. Z. F., & Silvaraju M. (2023). Comparison between the effect
21. of immersive virtual reality training versus conventional rehabilitation on limb loading and functional outcomes in patients after anterior
22. cruciate ligament reconstruction: A prospective randomized controlled trial. Asia-Pacific Journal of Sports Medicine, Arthroscopy, Rehabilitation and
23. Technology, 34, 28–37. https://doi.org/10.1016/j.asmart.2023.09.002
24. Jager, E. W. H., Inganäs, O., & Lundström, I. (2000). Microrobots for micrometer-size objects in aqueous media: Potential tools for single-cell manipulation. Science, 288(5475), 2335–2338. https://doi.org/10.1126/science.288.5475.2335
25. Jenkins, L., & Weerasekera, R. (2022). Sport-related back injury prevention with a wearable device. Biosensors and Bioelectronics: X, 11. https://doi.org/10.1016/j.biosx.2022.100202
26. Khuyen, N. Q., Kiefer, R., Elhi, F., Anbarjafari, G., Martinez, J. G., & Tamm, T. (2020). A biomimetic approach to increasing soft actuator performance by friction reduction. Polymers, 12(5). https://doi.org/10.3390/POLYM12051120
27. Kovoor, M., Durairaj, M., Karyakarte, M. S., Zair Hussain, M., Ashraf, M., & Maguluri, L. P. (2024). Sensorenhanced wearables and automated analytics
28. for injury prevention in sports. Measurement: Sensors, 32, 101054. https://doi.org/10.1016/j. measen.2024.101054
29. Li, Y., Kim, M., & Palkar, J. (2022). Using emerging technologies to promote creativity in education: A systematic review. International Journal
30. of Educational Research Open, 3. https://doi.org/10.1016/j.ijedro.2022.100177
31. Liu, Y., & Cao, S. (2024). The analysis of aerobics intelligent fitness system for neurorobotics based on big data and machine learning. Heliyon, 10(12). https://doi.org/10.1016/j.heliyon.2024.e33191
32. Lopez‐barreiro, J., Alvarez‐sabucedo, L., Garcia‐soidan, J. L., & Santos‐gago, J. M. (2022). Use of Blockchain Technology in the Domain of Physical Exercise, Physical Activity, Sport, and Active Ageing: A Systematic Review. In International Journal of Environmental Research and Public Health (Vol.
33. , Issue 13). MDPI. https://doi.org/10.3390/ijerph19138129
34. Muniz-Pardos, B., Angeloudis, K., Guppy, F. M., Keramitsoglou, I., Sutehall, S., Bosch, A., Tanisawa, K., Hosokawa, Y., Ash, G. I., Schobersberger, W., Grundstein, A. J., Casa, D. J., Morrissey, M. C., Yamasawa, F., Zelenkova, I., Racinais, S., & Pitsiladis, Y. (2021). Wearable and telemedicine innovations for Olympic events and elite sport. In Journal of Sports Medicine and Physical Fitness (Vol. 61, Issue 8, pp. 1061–1072). Edizioni Minerva Medica. https://doi.org/10.23736/S0022-4707.21.12752-5
35. Nguyen, H. S., & Voznak, M. (2024). A Bibliometric Analysis of Technology in Digital Health: Exploring Health Metaverse and Visualizing Emerging
36. Healthcare Management Trends. IEEE Access, 12, 23887–23913. https://doi.org/10.1109/ACCESS.2024.3363165
37. Petrović, L. T., Milovanović, D., & Desbordes, M. (2015). Emerging technologies and sports events: Innovative information and communication solutions.
38. Sport, Business and Management: An International Journal, 5(2), 175–190. https://doi.org/10.1108/SBM-06-2012-0021
39. Putranto, J. S., Heriyanto, J., Kenny, Achmad, S., & Kurniawan, A. (2022). Implementation of virtual reality technology for sports education and
40. training: Systematic literature review. Procedia Computer Science, 216, 293–300. https://doi.org/10.1016/j.procs.2022.12.139
41. Qie, X. (2023). Feedback delay of sports intelligent learning system based on model predictive control and artificial intelligence. Measurement: Sensors, 30. https://doi.org/10.1016/j.measen.2023.100922
42. Qiu, Y., Liu, G., Muthu, B. A., & Sivaparthipan, C. B. (2022). Design of an energy- efficient IoT device with optimized data management in sports person
43. health monitoring application. Transactions on Emerging Telecommunications Technologies, 33(10). https://doi.org/10.1002/ett.4258
44. Ramirez-GarciaLuna, J. L., Bartlett, R., Arriaga-Caballero, J. E., Fraser, R. D. J., & Saiko, G. (2022). Infrared Thermography in Wound Care, Surgery, and Sports Medicine: A Review. In Frontiers in Physiology (Vol.13). Frontiers Media S.A. https://doi.org/10.3389/fphys.2022.838528
45. Roggio, F., Bianco, A., Palma, A., Ravalli, S., Maugeri, G., Rosa, M. Di, & Musumeci, G. (2021). Technological advancements in the analysis of human motion and posture management through digital devices. World Journal of Orthopedics, 12(7), 467–484. https://doi.org/10.5312/wjo.v12.i7.467
46. Seshadri, D. R., Magliato, S., Voos, J. E., & Drummond, C. (2019). Clinical translation of biomedical sensors for sports medicine. In Journal of Medical Engineering and Technology (Vol. 43, Issue 1, pp. 66–81). Taylor and Francis Ltd. https://doi.org/10.1080/03091902.2019.1612474
47. Stevens, E., Espitia, F., Santo, U., Seccional, T., Julian, T., Triana, C., Universidad, Q., Tomas, S., & Tunja, S. (2023). Tecnología Vestible para Evaluar
48. Capacidades Físicas de Fuerza y Velocidad de Ejecución en Deportistas: Revisión Narrativa.
49. Tenforde, A. S., Iaccarino, M. A., Borgstrom, H., Hefner, J. E., Silver, J., Ahmed, M., Babu, A. N., Blauwet, C. A., Elson, L., Eng, C., Kotler, D., Homer, S., Makovitch, S., McInnis, K. C., Vora, A., & Borg- Stein, J. (2020). Telemedicine During COVID-19 for Outpatient Sports and Musculoskeletal Medicine
50. Physicians. PM and R, 12(9), 926–932. https://doi.org/10.1002/pmrj.12422
51. Van Biemen, T., Müller, D., & Mann, D. L. (2023). Virtual reality as a representative training environment for football referees. Human Movement Science,
52. https://doi.org/10.1016/j.humov.2023.103091
53. Wang, J. (2012). Research on application of virtual reality technology in competitive sports. Procedia Engineering, 29, 3659–3662. https://doi.org/10.1016/j.proeng.2012.01.548
54. Wang, X., & Guo, Y. (2023). The intelligent football players’ motion recognition system based on convolutional neural network and big data. Heliyon, 9(11).
55. https://doi.org/10.1016/j.heliyon.2023.e22316
56. Wei, S., Huang, P., Li, R., Liu, Z., & Zou, Y. (2021). Exploring the Application of Artificial Intelligence in Sports Training: A Case Study Approach. Complexity, 2021. https://doi.org/10.1155/2021/4658937
57. Yang, Y. (2024). Application of wearable devices based on artificial intelligence sensors in sports human health monitoring. Measurement: Sensors,
58. , 101086. https://doi.org/10.1016/j.measen. 2024.101086
59. Ye, S., Feng, S., Huang, L., & Bian, S. (2020). Recent Progress in Wearable Biosensors: From Healthcare Monitoring to Sports Analytics. In Biosensors (Vol.
60. , Issue 12). MDPI. https://doi.org/10.3390/BIOS10120205
61. Yu, S. (2021). Application of Blockchain-Based Sports Health Data Collection System in the Development of Sports Industry. Mobile Information Systems,
62. https://doi.org/10.1155/2021/4663147
63. Zhang, Y., Pi, Y., Wang, Q., Long, X., Wan, S., Liu, P., & Liu, Y. (2024). Application of video behavior fast detection based on wearable motion sensor devices in sports training. Measurement: Sensors, 33, 101096. https://doi.org/10.1016/j.measen.2024.101096
64. Zhou, L. (2021). Molecularly Imprinted Sensor based on Ag-Au NPs/SPCE for Lactate Determination in Sweat for Healthcare and Sport Monitoring.
65. International Journal of Electrochemical Science, 16, 1–13. https://doi.org/10.20964/2021.10.54