Fabrication and Characterization of Biological Biosensors in Sports Injury Treatment: High Sensitivity of Silver Oxide Using Artificial Neural Network Modeling

dc.authorscopusid 59903554000
dc.authorscopusid 55235052400
dc.authorscopusid 56369265300
dc.authorscopusid 23028598900
dc.authorscopusid 59903716800
dc.contributor.author Wu, Y.
dc.contributor.author Moghadas, B.K.
dc.contributor.author Gu, D.
dc.contributor.author Salahshour, S.
dc.contributor.author Hashemi, M.
dc.date.accessioned 2025-06-15T22:09:07Z
dc.date.available 2025-06-15T22:09:07Z
dc.date.issued 2025
dc.department Okan University en_US
dc.department-temp [Wu Y.] Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China, University of Science and Technology of China, Hefei, 230026, China, Hefei Normal University, Hefei, 230601, China; [Moghadas B.K.] Department of Chemical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran, Department of Applied Researches, Chemical, Petroleum & Polymer Engineering Research Center, Shiraz Branch, Islamic Azad University, Shiraz, Iran; [Gu D.] Department of Sports Medicine, Senior Department of Orthopedics, The Fourth Medical Center of PLA General Hospital, Beijing, 100048, China; [Salahshour S.] Faculty of Engineering and Natural Sciences, Istanbul Okan University, Istanbul, Turkey, Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey, Research Center of Applied Mathematics, Khazar University, Baku, Azerbaijan; [Hashemi M.] Fast Computing Center, Shabihsazan Ati Pars, Tehran, Iran en_US
dc.description.abstract This study focuses on the potential of biosensor technology to revolutionize sports injury management. Conventional methods for sports injury management, such as physical examinations and imaging techniques, often lack the sensitivity and real-time monitoring capabilities required to track the healing process effectively. These methods are also invasive, relying on blood sampling, which can be uncomfortable for athletes. In contrast, the proposed wearable biosensor offers a non-invasive, painless alternative by measuring biomarkers like myoglobin and creatine kinase in sweat. This study introduces a novel graphene field-effect transistor biosensor integrated into a wristband, combined with an artificial neural network (ANN) model to predict material properties and optimize biomarker detection. The results show the potential of this technology to revolutionize sports injury management by providing real-time, accurate, and non-invasive monitoring of injury progression and recovery. The results indicate that changes in compressive strength and porosity have an impact on dissolution rate, pore size growth, and chemical stability. Lower compressive strength leads to an increase in dissolution rate, while higher compressive strength promotes pore size growth and chemical stability. The accuracy of the ANN model's predictions was evaluated using linear regression and demonstrated acceptable error levels compared to experimental testing. Among the nanocomposite hydrogel scaffolds containing silver oxide nanoparticles, a specific sample showed noteworthy characteristics, including a compressive strength of 2.4 Mega Pascal, 55 % porosity, 22 % dissolution rate, 27 % pore size growth, and 65 % chemical stability. © 2025 Elsevier Ltd en_US
dc.description.sponsorship Anhui Office of Philosophy and Social Science, (2024AH053108); Anhui Office of Philosophy and Social Science en_US
dc.identifier.doi 10.1016/j.engappai.2025.111120
dc.identifier.issn 0952-1976
dc.identifier.scopus 2-s2.0-105005499055
dc.identifier.scopusquality Q1
dc.identifier.uri https://doi.org/10.1016/j.engappai.2025.111120
dc.identifier.uri https://hdl.handle.net/20.500.14517/8023
dc.identifier.volume 156 en_US
dc.identifier.wosquality Q1
dc.language.iso en en_US
dc.publisher Elsevier Ltd en_US
dc.relation.ispartof Engineering Applications of Artificial Intelligence en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Artificial Neural Network en_US
dc.subject Biomarkers And Sports en_US
dc.subject Materials Characterization en_US
dc.subject Nanoparticle Biosensors en_US
dc.title Fabrication and Characterization of Biological Biosensors in Sports Injury Treatment: High Sensitivity of Silver Oxide Using Artificial Neural Network Modeling en_US
dc.type Article en_US

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