Explorando a tendência de investigação e desenvolvimento de tecnologia em ciências do desporto nas últimas 4 décadas: revisão sistemática
DOI:
https://doi.org/10.47197/retos.v61.109306Palavras-chave:
technological advancements, sensor technology, big data analytics, virtual reality in sportsResumo
Este estudo analisa sistematicamente as tendências e a evolução da tecnologia da ciência do desporto nas últimas quatro décadas. Através de uma análise sistemática abrangente de 1.127 artigos da base de dados SCOPUS, pretendemos identificar as principais áreas temáticas, os países contribuintes e os padrões de palavras-chave predominantes neste campo. A análise destaca um aumento significativo de publicações e citações, indicando a crescente importância e reconhecimento da tecnologia da ciência do desporto. O Japão lidera as contribuições com maior número de publicações e citações, seguido pelos Estados Unidos e pela China. A medicina e a engenharia surgem como as áreas temáticas mais influentes, o que sublinha a natureza interdisciplinar da investigação. A análise de palavras-chave revelou uma forte ênfase nos estudos humanos, no desporto e na integração da ciência e da tecnologia, refletindo o cenário em mudança do campo. Os resultados mostram que os avanços tecnológicos, como a tecnologia de sensores, a análise de big data e a realidade virtual, revolucionaram a ciência do desporto, melhorando a monitorização do desempenho, a prevenção de lesões e os processos de reabilitação. O estudo identifica tendências críticas e fornece informações sobre futuras direções de investigação, defendendo a colaboração interdisciplinar contínua e a cooperação global para avançar ainda mais no campo. Estas reflexões oferecem uma visão global do estado histórico e atual da tecnologia da ciência do desporto e servem de roteiro para futuras inovações e aplicações. Ao compreender o desenvolvimento e as tendências atuais na tecnologia da ciência do desporto, os investigadores e os profissionais podem planear e implementar melhor estratégias eficazes para melhorar o desempenho desportivo e a saúde, contribuindo, em última análise, para o campo mais amplo da ciência e da tecnologia desportiva.
Palavras-chave: avanços tecnológicos, tecnologia de sensores, análise de big data, realidade virtual no desporto
Referências
Ae, M. (2020). The next steps for expanding and developing sport biomechanics. Sports Biomechanics, 19(6), 701–722. https://doi.org/10.1080/14763141.2020.1743745
An, D.-S., Moon, K.-S., Kang, M.-Y., & Yang, C.-H. (2016). Relationship among the motivation of foreign participants in international taekwondo event image, and participation satisfaction. Indian Journal of Science and Technology, 9(41). https://doi.org/10.17485/ijst/2016/v9i41/103859
Aquino, R., Carling, C., Palucci Vieira, L. H., Martins, G., Jabor, G., Machado, J., … Puggina, E. (2020). Influence of Situational Variables, Team Formation, and Playing Position on Match Running Performance and Social Network Analysis in Brazilian Professional Soccer Players. Journal of Strength and Conditioning Research, 34(3), 808–817. https://doi.org/10.1519/JSC.0000000000002725
Ashley, K. (2020). Applied Machine Learning for Health and Fitness: A Practical Guide to Machine Learning with Deep Vision, Sensors and IOT. In Applied Machine Learning for Health and Fitness: A Practical Guide to Machine Learning with Deep Vision, Sensors and IoT. Belmont, CA, United States: Springer. https://doi.org/10.1007/978-1-4842-5772-2
Balagué, N., Torrents, C., Hristovski, R., & Kelso, J. A. S. (2017). Sport science integration: An evolutionary synthesis. European Journal of Sport Science, 17(1), 51–62. https://doi.org/10.1080/17461391.2016.1198422
Bastida Castillo, A., Gómez Carmona, C. D., De la cruz sánchez, E., & Pino Ortega, J. (2018). Accuracy, intra- and inter-unit reliability, and comparison between GPS and UWB-based position-tracking systems used for time–motion analyses in soccer. European Journal of Sport Science, 18(4), 450–457. https://doi.org/10.1080/17461391.2018.1427796
Brazil, A., Exell, T., Wilson, C., & Irwin, G. (2020). A biomechanical approach to evaluate overload and specificity characteristics within physical preparation exercises. Journal of Sports Sciences, 38(10), 1140–1149. https://doi.org/10.1080/02640414.2020.1743065
Buyrukoğlu, E., & Bayindir, M. (2023). A Research on the Use of Wearable Technological Sports Products in Sports Sciences. Tekstil ve Muhendis, 30(131), 201–209. https://doi.org/10.7216/teksmuh.1282117
Carling, C., & Court, M. (2013). Match and motion analysis. In Science and Soccer: Developing Elite Performers, Third Edi-tion (pp. 173–198). University of Central Lancashire, Lille Football Club, United Kingdom: Taylor and Francis. https://doi.org/10.4324/9780203131862
Chen, F. (2021). Athlete muscle measurement and exercise data monitoring based on embedded system and wearable devices. Microprocessors and Microsystems, 82. https://doi.org/10.1016/j.micpro.2021.103901
Chen, Z. (2016). Development and testing of sensor-based real-time data acquisition system of discus motion parame-ters. Sensor Letters, 14(11), 1084–1088. https://doi.org/10.1166/sl.2016.3744
Cooper, R. A., & De Luigi, A. J. (2014). Adaptive sports technology and biomechanics: Wheelchairs. PM and R, 6(8 SUPPL.). https://doi.org/10.1016/J.PMRJ.2014.05.020
da Silva, J. C. G., Silva, K. F., Batista, C. E. C. F., Patrício, G. T., & Batista, G. R. (2023). Development of prototypes in sport: A systematic review. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology. https://doi.org/10.1177/17543371231189920
de Crignis, A. C., Ruhnau, S. T., Hösl, M., Lefint, J., Amberger, T., Dressnandt, J., … Müller, F. (2023). Robotic arm training in neurorehabilitation enhanced by augmented reality – a usability and feasibility study. Journal of NeuroEngi-neering and Rehabilitation, 20(1), 105. https://doi.org/10.1186/s12984-023-01225-5
Di Tocco, J., Massaroni, C., Raiano, L., Formica, D., & Schena, E. (2020). A wearable system for respiratory and pace monitoring in running activities: A feasibility study. 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 - Proceedings, 44–48. Unit of Measurements and Biomedical Instrumentation, Univer-sità Campus Bio-Medico di Roma, Rome, Italy: Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/MetroInd4.0IoT48571.2020.9138234
Enomoto, I. (2016). Relationship between physical fitness characteristics and sports experience in childhood and adoles-cence among Japanese Female University students. In Physical Activity Effects on the Anthropological Status of Children, Youth and Adults (pp. 117–128). Kamakura Women’s University, Kanagawa, Japan: Nova Science Publishers, Inc. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019898631&partnerID=40&md5=e14e41464ffcdbeb2592898366eef42a
Feng, Y., Jin, D., Shao, Q., Niu, J., Vladareanu, L., & Wang, H. (2020). Game scene construction for lower limb reha-bilitation robot based on virtual reality. Proceedings - 2020 5th International Conference on Electromechanical Control Tech-nology and Transportation, ICECTT 2020, 74–78. https://doi.org/10.1109/ICECTT50890.2020.00024
Figueredo, Y. O. C., Giraud, B. Y. J., Orihuela, R. A. V, Sánchez, M. T., & Ceballos, J. J. M. (2022). Design Commu-nity Projects as A Specific Professional Skill from The CTS Vision. Universidad y Sociedad, 14(4), 654–663. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131100346&partnerID=40&md5=1a09c2a897acfd81209062d86690d61f
Gamble, P., Chia, L., & Allen, S. (2020). The illogic of being data-driven: reasserting control and restoring balance in our relationship with data and technology in football. Science and Medicine in Football, 4(4), 338–341. https://doi.org/10.1080/24733938.2020.1854842
Gokeler, A., Bisschop, M., Myer, G. D., Benjaminse, A., Dijkstra, P. U., van Keeken, H. G., … Otten, E. (2016). Immersive virtual reality improves movement patterns in patients after ACL reconstruction: implications for en-hanced criteria-based return-to-sport rehabilitation. Knee Surgery, Sports Traumatology, Arthroscopy, 24(7), 2280–2286. https://doi.org/10.1007/S00167-014-3374-X/METRICS
Hamill, J., & Bates, B. T. (2023). Biomechanics and footwear research 1970–2000. Footwear Science, 15(2), 123–131. https://doi.org/10.1080/19424280.2023.2209045
Honma, H., Iida, Y., Okumura, Y., Fujii, K., & Kuno, Y. (2021). Implementation of VR-based personal basketball team-practice equipment. LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies, 207–208. Graduate Program of Mechatronics, Graduate School of Science and Engineering, Nanzan University, Nagoya, Ja-pan: Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/LifeTech52111.2021.9391886
Honma, H., Iida, Y., Okumura, Y., Fujii, K., & Umehira, M. (2022). Prototype development of VR based personal zone defense practice equipment. LifeTech 2022 - 2022 IEEE 4th Global Conference on Life Sciences and Technologies, 557–558. Nanzan University, Graduate Program of Mechatronics Graduate School of Science and Engineering, Na-goya, Japan: Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/LifeTech53646.2022.9754953
Hughes, M., & Bartlett, R. (2019). What is performance analysis? In Essentials of Performance Analysis in Sport: Third edition (pp. 11–20). Cardiff Metropolitan University, United Kingdom: Taylor and Francis. https://doi.org/10.4324/9780429340130-2
Ito, Y., Aoki, T., Sato, T., Oishi, K., & Ishii, K. (2020). Comparison of quadriceps setting strength and knee extension strength tests to evaluate lower limb muscle strength based on health-related physical fitness values in elderly people. BMJ Open Sport and Exercise Medicine, 6(1). https://doi.org/10.1136/bmjsem-2020-000753
Ivaschenko, A. V., Aleksandrova, M. V., Zheikov, D. S., Zakharova, E. V., & Kolsanov, A. V. (2024). Adaptation of virtual reality interfaces to psychological diagnosis and medical rehabilitation applications. Biomedical Engineering, 57(5), 340–342. https://doi.org/10.1007/S10527-023-10329-0/FIGURES/3
James, D., Lee, J., & Wheeler, K. (2019). Introduction to wearable sensors. SpringerBriefs in Applied Sciences and Technol-ogy, 1–6. https://doi.org/10.1007/978-981-13-3777-2_1
Kanschik, D., Bruno, R. R., Wolff, G., Kelm, M., & Jung, C. (2023). Virtual and augmented reality in intensive care medicine: a systematic review. Annals of Intensive Care, 13(1), 81. https://doi.org/10.1186/s13613-023-01176-z
Kaur, N. (2023). The Effect of Virtual and Augmented Reality on Well-Being: Perspectives in Mental Health Education. Lecture Notes in Networks and Systems, 588, 525–534. https://doi.org/10.1007/978-981-19-7982-8_44
Keen, R. (2018). Nutrition-Related Considerations in Soccer: A Review. American Journal of Orthopedics (Belle Mead, N.J.), 47(12). https://doi.org/10.12788/ajo.2018.0100
Köhne, M., & Waibel, K. (2022). Winter sports nation Germany—injuries in alpine ski racing and mass sports: Statis-tics and injury mechanisms in winter sports and current trends in sports science. Orthopadie, 51(11), 929–938. https://doi.org/10.1007/s00132-022-04313-x
Kristiyanto, A., Prasetyo, Y., Pratama, K. W., Karakauki, M., Mustapha, A., & Idrus, S. Z. S. (2020). Access to the Utilization of Science and Technology of Sports and Familiarity of the Sports Community towards Technologically Based Devices. Journal of Physics: Conference Series, 1529(2). Faculty of Sports, Sebelas Maret University, Insinyur Sutami No. 36 A Kentingan, Jebres, Surakarta City, Central Java 57126, Indonesia: IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1529/2/022099
Lease, B. A., Lim, K. H., Phang, J. T. S., & Chiam, D. H. (2024). Enhancing Sports Analytics through Web-Based Ap-plication: A Workflow Perspective. 2024 International Conference on Green Energy, Computing and Sustainable Technolo-gy, GECOST 2024, 282–286. https://doi.org/10.1109/GECOST60902.2024.10475000
Lee, J. W., Song, S., Kim, Y., Park, S.-B., & Han, D. H. (2023). Soccer’s AI transformation: deep learning’s analysis of soccer’s pandemic research evolution. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1244404
Liang, J., & He, Q. (2023). Application of artificial intelligence wearable devices based on neural network algorithm in mass sports activity evaluation. Soft Computing, 27(14), 10177–10188. https://doi.org/10.1007/s00500-023-08249-y
Liu, C., Hao, W., & Huo, B. (2023). Advances and challenges in sports biomechanics. Advances in Mechanics, 53(1), 198–238. https://doi.org/10.6052/1000-0992-22-030
Liu, H., Zhang, W., Hu, D., & Zhang, H. (2016). Nanometer technology and the development of competitive sports in China. International Journal of Simulation: Systems, Science and Technology, 17(25). https://doi.org/10.5013/IJSSST.a.17.25.04
Liu, Y., & Liu, L. (2023). Analysis of auxiliary modes for sports intelligence training system based on nonlinear model optimization and improved algorithms. Soft Computing. https://doi.org/10.1007/s00500-023-08546-6
Massaroni, C., Di Tocco, J., Sabbadini, R., Carnevale, A., Lo Presti, D., Schena, E., … Sterzi, S. (2020). Influence of torso movements on a multi-sensor garment for respiratory monitoring during walking and running activities. I2MTC 2020 - International Instrumentation and Measurement Technology Conference, Proceedings. Univ. Campus Bio-Medico di Roma, Unit of Measurements, Rome, Italy: Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/I2MTC43012.2020.9128754
Massaroni, C., Zaltieri, M., Presti, D. L., Nicolò, A., Tosi, D., & Schena, E. (2021). Fiber Bragg grating sensors for cardiorespiratory monitoring: A review. IEEE Sensors Journal, 21(13), 14069–14080. https://doi.org/10.1109/JSEN.2020.2988692
Mehta, S. (2019). Relationship between workload and throwing injury in varsity baseball players. Physical Therapy in Sport, 40, 66–70. https://doi.org/10.1016/j.ptsp.2019.08.001
Moylan, E. C., & Horne, G. (2013). A new era in sports science: The launch of BMC sports science, medicine and re-habilitation. BMC Sports Science, Medicine and Rehabilitation, 5(1). https://doi.org/10.1186/2052-1847-5-1
Müller, S., Dekker, E., Morris-Binelli, K., Piggott, B., Hoyne, G., Christensen, W., … Hambrick, D. Z. (2023). At-tributes of Expert Anticipation Should Inform the Design of Virtual Reality Simulators to Accelerate Learning and Transfer of Skill. Sports Medicine, 53(2), 301–309. https://doi.org/10.1007/s40279-022-01735-7
Neshitov, A., Tyapochkin, K., Kovaleva, M., Dreneva, A., Surkova, E., Smorodnikova, E., & Pravdin, P. (2023). Esti-mation of cardiorespiratory fitness using heart rate and step count data. Scientific Reports, 13(1), 15808. https://doi.org/10.1038/s41598-023-43024-x
Park, C., & Moon, J. (2013). Using Game Technology to Develop Snowboard Training Simulator. Communications in Computer and Information Science, 374(PART II), 723–726. Dept. of Game Engineering, Hoseo University, Asan, Chungnam, 336-795, 165 Sechul-ri, Baebang-myun, South Korea: Springer Verlag. https://doi.org/10.1007/978-3-642-39476-8_145
Park, M.-J., & Park, T.-S. (2019). A systematic review on the convergence of contents in taekwondo performance and virtual reality technology. Asia Life Sciences, 28(2), 217–229. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074231123&partnerID=40&md5=207890cbd6a32f86a5550c910d14c333
Park, S. H., & Silva, M. (2004). Neuromuscular electrical stimulation enhances fracture healing: Results of an animal model. Journal of Orthopaedic Research, 22(2), 382–387. https://doi.org/10.1016/J.ORTHRES.2003.08.007
Rajendran, S. B., Challen, K., Wright, K. L., & Hardy, J. G. (2021). Electrical stimulation to enhance wound healing. Journal of Functional Biomaterials, 12(2). https://doi.org/10.3390/JFB12020040
Reis, F., Sá-Moura, B., Guardado, D., Couceiro, P., Catarino, L., Mota-Pinto, A., … Malva, J. O. (2019). Develop-ment of a Healthy Lifestyle Assessment Toolkit for the General Public. Frontiers in Medicine, 6. https://doi.org/10.3389/fmed.2019.00134
Ren, Y., & Li, J. (2021). The Conception of Application of Computer Virtual Reality Technology in Sports Training. Journal of Physics: Conference Series, 1861(1). Capital University of Physical Education and Sports, Beijing, 100091, China: IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1861/1/012110
Renner, E., Lang, N., Langenstein, B., Struck, M., & Bertsch, T. (2020). Validating sweat ammonia as physiological parameter for wearable devices in sports science. Proceedings of the Annual International Conference of the IEEE Engineer-ing in Medicine and Biology Society, EMBS, 2020-July, 4644–4647. Friedrich-Alexander University Erlangen-Nürnberg (FAU), Institute of Microwaves and Photonics, Erlangen, 91058, Germany: Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/EMBC44109.2020.9175434
Rossi, A., Perri, E., Trecroci, A., Savino, M., Alberti, G., & Iaia, F. M. (2017). GPS data reflect players’ internal load in soccer. In G. R., K. G., R. V., W. X., M. L., A. S., … D. G. (Eds.), IEEE International Conference on Data Mining Workshops, ICDMW (Vol. 2017-Novem, pp. 890–893). Dept. of Biomedical Science for Health, Uninversit Degli Dtudi di Milano, Milan, Italy: IEEE Computer Society. https://doi.org/10.1109/ICDMW.2017.122
Sangeethalakshmi, K., Sasi Kumar, C., Lakshmi, V. V., Giriprasad, S., Malathi, N., & Velmurugan, S. (2023). Smart Biomechanics System with IoT and Cloud Computing for Injury Prevention and Muscle Fatigue Analysis. 2023 3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023. https://doi.org/10.1109/SMARTGENCON60755.2023.10442220
Schweinbenz, A. N. (2016). Sport training, sport science, and technology. In The Routledge History of American Sport (pp. 345–357). Laurentian University, Canada: Taylor and Francis. https://doi.org/10.4324/9781315767123-40
Scott, M. J., Summerley, R., Besombes, N., Connolly, C., Gawrysiak, J., Halevi, T., … Patrick Williams, J. (2021). Towards a Framework to Support the Design of Esports Curricula in Higher Education. Annual Conference on Innova-tion and Technology in Computer Science Education, ITiCSE, 599–600. Falmouth University, United Kingdom: Associa-tion for Computing Machinery. https://doi.org/10.1145/3456565.3461440
Shushardzhan, S. V., Eremina, N., Shushardzhan, R., Allik, T., & Mukasheva, K. (2023). Scientific Music Therapy Technologies for Psychological Care and Rehabilitation in the COVID-19 Pandemic. Lecture Notes in Networks and Sys-tems, 448, 627–637. https://doi.org/10.1007/978-981-19-1610-6_55
Slaughter, P. R., & Adamczyk, P. G. (2020). Tracking quantitative characteristics of cutting maneuvers with wearable movement sensors during competitive women’s ultimate frisbee games. Sensors (Switzerland), 20(22), 1–17. https://doi.org/10.3390/s20226508
Song, Y., Sárosi, J., Cen, X., & Bíró, I. (2023). Human motion analysis and measurement techniques: current applica-tion and developing trend. Analecta Technica Szegedinensia, 17(2), 48–58. https://doi.org/10.14232/ANALECTA.2023.2.48-58
Thomas, S. V., & Gilbert, J. E. (2016). Integrating Technology to Enhance Athlete Development: A Literature Review. Journal of Higher Education Athletics & Innovation, 1, 73–84. https://doi.org/10.15763/ISSN.2376-5267.2016.1.1.73-84
Toto, G. A. (2022). A Systematic Review on Digital Technologies on Sport Science: Didactic of Sport. Formazione & Insegnamento, 20(1 Suppl.), 001–012. https://doi.org/10.7346/-feis-XX-01-22_01
Tsumori, T. (2013). [Introduction of Shimane University’s outside funded support project for female researchers and healthcare staff]. Kaibogaku zasshi. Journal of anatomy, 88(4), 61–66. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891499061&partnerID=40&md5=7c8641dd06726aba7bf4627429582341
Vellios, E. E., Pinnamaneni, S., Camp, C. L., & Dines, J. S. (2020). Technology Used in the Prevention and Treatment of Shoulder and Elbow Injuries in the Overhead Athlete. Current Reviews in Musculoskeletal Medicine, 13(4), 472–478. https://doi.org/10.1007/s12178-020-09645-9
Wang, G. (2023). Hot Topics of Molecular and Cellular Biomechanics in 2022. Molecular & Cellular Biomechanics, 20(2), 63–66. https://doi.org/10.32604/MCB.2023.044564
Wang, J., & Liu, B. (2023). Analyzing the feature extraction of football player’s offense action using machine vision, big data, and internet of things. Soft Computing, 27(15), 10905–10920. https://doi.org/10.1007/s00500-023-08735-3
Xie, X. J., Xiang, J. J., & Liu, L. M. (2013). The application of sensor technology in physical training. Applied Mechanics and Materials, 336–338, 144–147. College of Physical Education and Health, Chongqing There Gorges College, Wan Zhou, China. https://doi.org/10.4028/www.scientific.net/AMM.336-338.144
Xu, Y., Huang, J., Yao, Y., & Zeng, C. (2022). Construction of Sports Rehabilitation Training Method Based on Virtual Reality. Journal of Circuits, Systems and Computers, 32(02), 2350034. https://doi.org/10.1142/S0218126623500342
Zhang, Y., & Tsai, S. B. (2021). Application of Adaptive Virtual Reality with AI-Enabled Techniques in Modern Sports Training. Mobile Information Systems, 2021(1), 6067678. https://doi.org/10.1155/2021/6067678
Zhen, L., Wang, L., & Hao, Z. (2015). A biomechanical analysis of basketball shooting. International Journal of Simulation: Systems, Science and Technology, 16(3B), 1.1-1.5. https://doi.org/10.5013/IJSSST.a.16.3B.01
Zrenner, M., Küderle, A., Roth, N., Jensen, U., Dümler, B., & Eskofier, B. M. (2020). Does the position of foot-mounted imu sensors influence the accuracy of spatio-temporal parameters in endurance running? Sensors (Switzer-land), 20(19), 1–21. https://doi.org/10.3390/s20195705
Zsidai, B., Hilkert, A.-S., Kaarre, J., Narup, E., Senorski, E. H., Grassi, A., … Feldt, R. (2023). A practical guide to the implementation of AI in orthopaedic research – part 1: opportunities in clinical application and overcoming ex-isting challenges. Journal of Experimental Orthopaedics, 10(1), 117. https://doi.org/10.1186/s40634-023-00683-z
Downloads
Publicado
Como Citar
Edição
Secção
Licença
Direitos de Autor (c) 2024 Retos
Este trabalho encontra-se publicado com a Licença Internacional Creative Commons Atribuição-NãoComercial-SemDerivações 4.0.
Autores que publicam nesta revista concordam com os seguintes termos:
- Autores mantém os direitos autorais e assegurar a revista o direito de ser a primeira publicação da obra como licenciado sob a Licença Creative Commons Attribution que permite que outros para compartilhar o trabalho com o crédito de autoria do trabalho e publicação inicial nesta revista.
- Os autores podem estabelecer acordos adicionais separados para a distribuição não-exclusiva da versão do trabalho publicado na revista (por exemplo, a um repositório institucional, ou publicá-lo em um livro), com reconhecimento de autoria e publicação inicial nesta revista.
- É permitido e os autores são incentivados a divulgar o seu trabalho por via electrónica (por exemplo, em repositórios institucionais ou no seu próprio site), antes e durante o processo de envio, pois pode gerar alterações produtivas, bem como a uma intimação mais Cedo e mais do trabalho publicado (Veja O Efeito do Acesso Livre) (em Inglês).
Esta revista é a "política de acesso aberto" de Boai (1), apoiando os direitos dos usuários de "ler, baixar, copiar, distribuir, imprimir, pesquisar, ou link para os textos completos dos artigos". (1) http://legacy.earlham.edu/~peters/fos/boaifaq.htm#openaccess
