Enhancing athletic performance and well-being: The role of RFID Technology in health monitoring and sports psychology
Abstract
This study examined the integration of Radio-Frequency Identification (RFID) technology into sports psychology to enhance the monitoring and support of athletes' physical and mental performance. The review focused specifically on technologies used in sport performance and sport psychology contexts. Two groups of technologies were considered: 1) Wearable sensors. 2) RFID-based systems. Through the use of RFID-enabled wearable sensors, athletes can be tracked non-intrusively, providing real-time data on physiological markers such as heart rate, skin temperature, and muscle activity, as well as psychological indicators like stress levels and emotional states. RFID technology enables the collection of data without direct contact, offering new possibilities for understanding the complex interactions between physical exertion and mental resilience. By combining RFID with the Internet of Things (IoT), this approach allows for continuous performance monitoring and personalized feedback, thereby helping athletes optimize their training and recovery strategies. This paper highlights the potential of RFID in sports psychology, underscoring its capability to improve athlete well-being and performance through innovative monitoring and tailored interventions.
Downloads
-
Abstract153
-
PDF36
References
1. Ahmad, W. N. W., Adib, M. A. H. M., Ahmad, Z., Zaihidee, F. M., & Txi, M. R. S. (2022). Integration of the Health Monitoring System with IoT Application in Sports Technology: A Review. Jurnal Kejuruteraan, 5(2), 101-109.
2. Ahmadihaji, A., Izquierdo, R., & Shih, A. (2023). From chip-based to chipless rfid sensors: a review. IEEE Sensors Journal, 23(11), 11356-11373.
3. Alzahrani, A., & Ullah, A. (2024). Advanced biomechanical analytics: Wearable technologies for precision health monitoring in sports performance. Digital Health, 10, 1-18. https://doi.org/10.1177/20552076241256745
4. Bardini, S., Ginestretti, L., Lazzari, J., & Santambrogio, M. D. (2024, July). Towards a Greater Awareness of the Relevance of Sleep and Physical Activity for Personal Well-Being. In 2024 IEEE International Workshop on Sport, Technology and Research (STAR) (pp. 109-114). IEEE. DOI: https://doi.org/10.1109/STAR62027.2024.10635937
5. Behera, S. K. (2021). Chipless RFID sensors for wearable applications: A review. IEEE Sensors Journal, 22(2), 1105-1120. https://doi.org/10.1109/JSEN.2021.3126487
6. Ben, X., Ren, Y., Zhang, J., Wang, S. J., Kpalma, K., Meng, W., & Liu, Y. J. (2021). Video based facial micro-expression analysis: A survey of datasets, features and algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(9), 5826-5846 https://doi.org/10.1109/TPAMI.2021.3067464
7. Biswas, S., Roy, M., Mondal, A., & Karmakar, R. (2024, May). Voice-Based Automated Detection of Mental Health Considering Comparative Performances of Multiple Machine Learning Models. In 2024 5th International Conference for Emerging Technology (INCET) (pp. 1-6). IEEE. https://doi.org/10.1109/INCET61516.2024.10592913
8. Cieśliński, W. B., Sobecki, J., Piepiora, P. A., Piepiora, Z. N., & Witkowski, K. (2016). Application of the augmented reality in prototyping the educational simulator in sport: The example of judo. Journal of Physics: Conference Series, 710(1), 1-8. https://doi.org/10.1088/1742-6596/710/1/012016
9. Civeriati, V., Pugliese, B. L., Carraro, C., Corniani, G., Bauducco, F., Angelucci, A., et al. (2024). A sensorized insole to estimate ground reaction forces and center of pressure during gait. In 2024 IEEE International Workshop on Sport, Technology and Research (STAR) (pp. 21–25). IEEE. https://doi.org/10.1109/STAR62027.2024.10636002
10. Colella, R., Mannini, L., Tumolo, M. R., Sabina, S., Molinaro, V., Ranavolo, A., et al. (2022). RFID-based sensing and reconstruction of human movements for safety monitoring of workers. In 2022 IEEE 12th International Conference on RFID Technology and Applications (RFID-TA) (pp. 184–186). IEEE. https://doi.org/10.1109/RFID-TA54958.2022.9924040
11. Colella, R., Sabina, S., Mincarone, P., & Catarinucci, L. (2023). Semi-passive RFID electronic devices with on-chip sensor fusion capabilities for motion capture and biomechanical analysis. IEEE Sensors Journal, 23(11), 11672-11681.
12. Cordeiro, M. C., Ó Catháin, C., & Rodrigues, T. B. (2022). The development of a machine learning/augmented reality immersive training system for performance monitoring in athletes. In Proceedings of the 14th International Workshop on Immersive Mixed and Virtual Environment Systems (pp. 19–22). https://doi.org/10.1145/3534086.3534332
13. Deshmukh, R. G., Pinjarkar, A., & Rana, A. K. (2022). IoT and wearable sensors for health monitoring. In Advanced sensing in image processing and IoT (pp. 137–152). CRC Press. https://doi.org/10.1201/9781003221333
14. Ding, Y., Tan, K., Sheng, L., Ren, H., Su, Z., Yang, H., Zhang, X., Li, J., & Hu, P. (2024). Integrated mental stress smartwatch based on sweat cortisol and HRV sensors. Biosensors & Bioelectronics, 265, 1-16. https://doi.org/10.1016/j.bios.2024.116691
15. Fullagar, H. H., Skorski, S., Duffield, R., Hammes, D., Coutts, A. J., & Meyer, T. (2015). Sleep and athletic performance: the effects of sleep loss on exercise performance, and physiological and cognitive responses to exercise. Sports Medicine, 45(2), 161-186. https://doi.org/10.1007/s40279-014-0260-0
16. Gaspari, F., & Quaranta, S. (2019). Nanostructured materials for RFID sensors. In Nanomaterials design for sensing applications (pp. 93–128). Elsevier. https://doi.org/10.1016/B978-0-12-814505-0.00003-5
17. Giles, S., Fletcher, D., Arnold, R., Ashfield, A., & Harrison, J. (2020). Measuring well-being in sport performers: where are we now and how do we progress?. Sports Medicine, 50(7), 1255-1270. https://doi.org/10.1016/B978-0-12-814505-0.00003-5
18. Gordon, A. M., & Mendes, W. B. (2021). A large-scale study of stress, emotions, and blood pressure in daily life using a digital platform. Proceedings of the National Academy of Sciences, 118(31), 1-7. https://doi.org/10.1073/pnas.2105573118
19. Han, L., & Hua, X. (2023). RFID Backscatter Based Sport Motion Sensing Using ECOC-Based SVM. Sensors, 23(17), 1-15. https://doi.org/10.3390/s23177324
20. Huifeng, W., Kadry, S. N., & Raj, E. D. (2020). Continuous health monitoring of sportsperson using IoT devices based wearable technology. Computer Communications, 160, 588-595. https://doi.org/10.1016/j.comcom.2020.04.025
21. Jerath, R., Syam, M., & Ahmed, S. (2023). The future of stress management: integration of smartwatches and HRV technology. Sensors, 23(17), 1-14. https://doi.org/10.3390/s23177314
22. Kim, S., Mariotti, C., Alimenti, F., Mezzanotte, P., Georgiadis, A., Collado, A., ... & Tentzeris, M. M. (2013). No battery required: Perpetual RFID-enabled wireless sensors for cognitive intelligence applications. IEEE Microwave Magazine, 14(5), 66-77. https://doi.org/10.1109/MMM.2013.2259398
23. Kovoor, M., Durairaj, M., Karyakarte, M. S., Hussain, M. Z., Ashraf, M., & Maguluri, L. P. (2024). Sensor-enhanced wearables and automated analytics for injury prevention in sports. Measurement Sensors, 32(19), 1-24. https://doi.org/10.1016/j.measen.2024.101054
24. Lange, D. H. (2021). U.S. Patent No. 10,952,638. Washington, DC: U.S. Patent and Trademark Office.
25. Lasantha, L., Khan, S. I., Ray, B., & Karmakar, N. C. (2024). Enhancing quality factor of chipless RFID sensors by optimising the substrate properties and resonator geometry. In 2024 IEEE International Conference on RFID (RFID) (pp. 125–130). IEEE. https://doi.org/10.1109/RFID62091.2024.10582558
26. Li, N., Zhou, R., Krishna, B., Pradhan, A., Lee, H., He, J., & Jiang, N. (2024). Non-invasive Techniques for Muscle Fatigue Monitoring: A Comprehensive Survey. ACM Computing Surveys, 56(9), 1-40. https://doi.org/10.1145/3648679
27. Li, R. T., Kling, S. R., Salata, M. J., Cupp, S. A., Sheehan, J., & Voos, J. E. (2016). Wearable performance devices in sports medicine. Sports Health, 8(1), 74-78. https://doi.org/10.1177/1941738115616917
28. Lin, J. (2024). Wearable Emotion Recognition Technology Based on Heart Rate Variability and EEG Rhythm. Transactions on Computer Science and Intelligent Systems Research, 5, 892-898. https://doi.org/10.62051/g4rwwf66
29. Miozzi, C., Errico, V., Marrocco, G., Gruppioni, E., & Saggio, G. (2020, June). RFID interface for compact pliable EMG wireless epidermal sensor. In 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT (pp. 202-206). IEEE. https://doi.org/10.1109/MetroInd4.0IoT48571.2020.9138182
30. Moniruzzaman, M., Yin, Z., Hossain, M. S. B., Choi, H., & Guo, Z. (2023). Wearable motion capture: Reconstructing and predicting 3D human poses from wearable sensors. IEEE Journal of Biomedical and Health Informatics, 27(11), 5345-5356. https://doi.org/10.1109/JBHI.2023.3311448
31. Mulloni, V., Marchi, G., Gaiardo, A., Valt, M., Donelli, M., & Lorenzelli, L. (2024). Applications of Chipless RFID Humidity Sensors to Smart Packaging Solutions. Sensors, 24(9), 1-12. https://doi.org/10.3390/s24092879
32. Nadeem, M., Habib, A., & Umair, M. Y. (2024). Chipless RFID based multi-sensor tag for printed electronics. Heliyon, 10(4), 1-17. https://doi.org/10.1016/j.heliyon.2024.e26494
33. Nguyen A. (2009). The potential implementation of radio-frequency identification technology for personal health examination and monitoring. McGill Journal of Medicine, 12(2), 67-72.
34. Occhiuzzi, C., Parrella, S., & Marrocco, G. (2020, August). Flexible dual chip on-skin RFID sensor for body temperature monitoring. In 2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS) (pp. 1-4). IEEE. https://doi.org/10.1109/FLEPS49123.2020.9239531
35. Plews, D. J., Laursen, P. B., Stanley, J., Kilding, A. E., & Buchheit, M. (2013). Training adaptation and heart rate variability in elite endurance athletes: opening the door to effective monitoring. Sports Medicine, 43, 773-781. https://doi.org/10.1007/s40279-013-0071-8
36. Qaim, W. B., Ometov, A., Molinaro, A., Lener, I., Campolo, C., Lohan, E. S., & Nurmi, J. (2020). Towards energy efficiency in the internet of wearable things: A systematic review. IEEE Access, 8, 175412-175435. https://doi.org/10.1109/ACCESS.2020.3025270
37. Raju, A. R., Ramadevi, R., Babu, P. R., & Vetriselvi, D. (2023, August). Galvanic Skin Response based Stress Detection System using Machine Learning and IoT. In 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) (pp. 709-714). IEEE. https://doi.org/10.1109/ICAISS58487.2023.10250663
38. Rennane, A., Abdelnour, A., Kaddour, D., Touhami, R., & Tedjini, S. (2017, August). Development of passive UHF RFID tag on flexible foil for sport balls pressure monitoring. In 2017 XXXIInd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS) (pp. 1-2). IEEE. https://doi.org/10.23919/URSIGASS.2017.8105164
39. Riente, A., Bianco, G. M., Fiore, L., Arduini, F., Marrocco, G., & Occhiuzzi, C. (2023, March). An RFID sensor with microfluidic for monitoring the pH of sweat during sport activity. In 2023 17th European Conference on Antennas and Propagation (EuCAP) (pp. 1-4). IEEE. https://doi.org/10.23919/EuCAP57121.2023.10133044
40. Roh, S., Nguyen, T. D., & Lee, J. S. (2024). Applications of Nanomaterials in RFID Wireless Sensor Components. Applied Sciences, 14(3), 1-28. https://doi.org/10.3390/app14031216
41. Satapathy, C., Gokhale, H., Syed, A. Z., & Nersisson, R. (2024, March). Galvanic skin response-based stress level detection using supervised machine learning approach. In AIP Conference Proceedings (Vol. 2966, No. 1). AIP Publishing. https://doi.org/10.1063/5.0189783
42. Scarpellini, A., Aliverti, A., & Esmailbeigi, H. (2024, July). A Wireless Intra-Oral Device for Respiratory and Cardiovascular Monitoring in Sport. In 2024 IEEE International Workshop on Sport, Technology and Research (STAR) (pp. 176-180). IEEE. https://doi.org/10.1109/STAR62027.2024.10635949
43. Seçkin, A. Ç., Ateş, B., & Seçkin, M. (2023). Review on Wearable Technology in sports: Concepts, Challenges and opportunities. Applied Sciences, 13(18), 1-39. https://doi.org/10.3390/app131810399
44. Seshadri, D. R., Li, R. T., Voos, J. E., Rowbottom, J. R., Alfes, C. M., Zorman, C. A., & Drummond, C. K. (2019). Wearable sensors for monitoring the internal and external workload of the athlete. NPJ Digital Medicine, 2, 1-12. https://doi.org/10.1038/s41746-019-0149-2
45. Shaffer, F., & Ginsberg, J. P. (2017). An overview of heart rate variability metrics and norms. Frontiers in Public Health, 5, 1-17. https://doi.org/10.3389/fpubh.2017.00258
46. Shah, J. V., Lautner, D. A., & Hor-Lao, M. K. (2017). U.S. Patent No. 9,740,899. Washington, DC: U.S. Patent and Trademark Office. https://patents.google.com/patent/US9740899B1/en
47. Shen, X., Shi, G., Cheng, L., Gu, L., Rao, Y., & He, Y. (2023). Chipless RFID-inspired Sensing for Smart Agriculture: A Review. Sensors and Actuators A: Physical, 363, 1-19. https://doi.org/10.1016/j.sna.2023.114725
48. Simbolon, M. E. M., Firdausi, D. K. A., Dwisaputra, I., Rusdiana, A., Pebriandani, C., & Prayoga, R. (2023). Utilization of Sensor technology as a Sport Technology Innovation in Athlete Performance Measurement: Research Trends. IJEIS (Indonesian Journal of Electronics and Instrumentation Systems), 13(2), 147-158. https://doi.org/10.22146/ijeis.89581
49. Song, Y., Min, J., Yu, Y., Wang, H., Yang, Y., Zhang, H., & Gao, W. (2020). Wireless battery-free wearable sweat sensor powered by human motion. Science Advances, 6(40), 1-12. https://doi.org/10.1126/sciadv.aay9842
50. Subrahmannian, A., & Behera, S. K. (2022). Chipless RFID sensors for IoT-based healthcare applications: A review of state of the art. IEEE Transactions on Instrumentation and Measurement, 71, 1-20. https://doi.org/10.1109/TIM.2022.3180422
51. Tariq, M. U. (2024). Advanced wearable medical devices and their role in transformative remote health monitoring. In Transformative Approaches to Patient Literacy and Healthcare Innovation (pp. 308-326). IGI Global. https://doi.org/10.4018/979-8-3693-3661-8.ch015
52. Wang, T., Dai, S., Liu, Y., & Ye, T. T. (2022). Battery-less sensing of body movements through differential backscattered RFID signals. IEEE Sensors Journal, 22(9), 8490-8498. https://doi.org/10.1109/JSEN.2022.3161406
53. Waqar, A., Ahmad, I., Habibi, D., & Phung, Q. V. (2021). Analysis of GPS and UWB positioning system for athlete tracking. Measurement: Sensors, 14(3), 1-16. https://doi.org/10.1016/j.measen.2020.100036
54. Wu, Y., Valdez, R., & Forlines, C. (2023, March). Cognitive and Emotional Monitoring with Inexpensive Wrist-Worn Consumer-Grade Wearables. In 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 665-670). IEEE. https://doi.org/10.1109/PerComWorkshops56833.2023.10150338
55. Xu, Q., Liu, X., Luo, J., & Tang, Z. (2020). Emotion monitoring with RFID: An experimental study. CCF Transactions on Pervasive Computing and Interaction, 2(4), 299-313. https://doi.org/10.1007/s42486-020-00043-1
56. Yan, D., Sun, X., Hu, S., & Zhang, K. (2023, November). Chipless RFID Humidity Sensor Based on Rectangular-Stub-Loaded SRR. In 2023 China Automation Congress (CAC) (pp. 539-543). IEEE. https://doi.org/10.1109/CAC59555.2023.10450927
57. Yu, Y., Qi, Z., Yi, D., Tang, M. C., & Ziolkowski, R. W. (2023). Miniaturized and highly sensitive epidermal RFID sensor for reliable skin temperature monitoring at a distance. IEEE Sensors Journal, 23(6), 5757-5765. https://doi.org/10.1109/JSEN.2023.3241155
58. Zhu, J. (2023). Real-time monitoring for sport and mental health prevention of college student based on wireless sensor network. Preventive Medicine, 173, 1-17. https://doi.org/10.1016/j.ypmed.2023.107581
The works and papers that are published in this Journal are subject to the following terms:
1. The Publication Service of the University of Murcia (the publisher) has the Publication Rights (Copyright) to the published papers and works, and favors and permits the reusing of the same under the license indicated in point 2.
© Servicio de Publicaciones, Universidad de Murcia, 2013
2. The papers and works are to be published in the digital edition of the Journal under the license Creative Commons Reconocimiento-No Comercial-Sin Obra Derivada 3.0 España (legal text). The copying, using, spreading, transmitting and publicly displaying of the papers, works or publication are permitted as long as: i) the authors and original sources (Journal, publisher and URL of the publication) are quoted; ii) it is not used for commercial benefit; iii) the existence and specifications of this users license are mentioned.
3. Conditions of Self-Archiving. It is permitted and encouraged that the authors spread electronically the pre-print (before printing) and/or post-print (the revised, evaluated and accepted) versions of their papers or works before their publication since this favors their circulation and early diffusion and therefore can help increase their citation and quotation, and also there reach through the academic community.
The works and papers that are published in this Journal are subject to the following terms:
1. The Publication Service of the University of Murcia (the publisher) has the Publication Rights (Copyright) to the published papers and works, and favors and permits the reusing of the same under the license indicated in point 2.
© Servicio de Publicaciones, Universidad de Murcia, 2013
2. The papers and works are to be published in the digital edition of the Journal under the license Creative Commons Reconocimiento-No Comercial-Sin Obra Derivada 3.0 España (legal text). The copying, using, spreading, transmitting and publicly displaying of the papers, works or publication are permitted as long as: i) the authors and original sources (Journal, publisher and URL of the publication) are quoted; ii) it is not used for commercial benefit; iii) the existence and specifications of this users license are mentioned.
3. Conditions of Self-Archiving. It is permitted and encouraged that the authors spread electronically the pre-print (before printing) and/or post-print (the revised, evaluated and accepted) versions of their papers or works before their publication since this favors their circulation and early diffusion and therefore can help increase their citation and quotation, and also there reach through the academic community.
