Sweat biosensors for sports monitoring / Biossensores de suor para monitoramento esportivo / Biosensores de sudor para la monitorización deportiva

ABSTRACT Introduction: Biometric sweat monitoring is an important tool for optimizing sports training. The possibility of developing a wearable amperometric lactate biosensor using a screen-printed carbon electrode (SPCE) impregnated by Ag nanoparticles (Ag NPs) for sweat determination in sports monitoring is questioned. Objective: To develop a sensor with GCE substrate coated on Ag NPs/SPCE. Methods: FESEM and XRD analysis were used for the morphological and structural characterizations of Ag and SPCE NPs, respectively. Results: FESEM, EDS, and XRD revealed that Ag NPs were uniformly dispersed in SPCE. The electrochemical biosensor responded linearly to lactate in phosphate buffer solutions, with detection and sensitivity limits of 1.2 µM and 14.2 mAcm-2 mM-1, respectively. Conclusion: The results suggest that Ag NPs/SPCE can be used to continuously monitor lactate levels in sweat as a practical and reliable biosensor for use. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

RESUMO Introdução: O monitoramento biométrico do suor é uma ferramenta importante para otimização do treino esportivo. Questiona-se a possibilidade do desenvolvimento de um biossensor amperométrico de lactato vestível utilizando eletrodo de carbono impresso em tela (SPCE) impregnado por nanopartículas Ag (Ag NPs) para determinação do suor no monitoramento esportivo. Objetivos: Desenvolver um sensor com substrato GCE revestido em Ag NPs/SPCE. Métodos: A análise FESEM e XRD foi utilizada para as caracterizações morfológicas e estruturais dos NPs de Ag e SPCE, respectivamente. Resultados: Os resultados da FESEM, EDS, XRD revelaram que os NPs de Ag estavam uniformemente dispersos em SPCE. O biossensor eletroquímico respondeu linearmente ao lactato em soluções tampão fosfato, com limites de detecção e sensibilidade de 1,2 µM e 14,2 mAcm-2 mM-1, respectivamente. Conclusão: Os resultados sugerem que o Ag NPs/SPCE pode ser utilizado para monitorar continuamente os níveis de ácido láctico no suor como um biossensor prático e confiável para o uso. Nível de evidência II; Estudos terapêuticos - investigação dos resultados do tratamento.

RESUMEN Introducción: La monitorización biométrica del sudor es una herramienta importante para la optimización del entrenamiento deportivo. Se cuestiona la posibilidad de desarrollar un biosensor de lactato amperométrico vestible utilizando un electrodo de carbono serigrafiado (SPCE) impregnado por nanopartículas de Ag (Ag NPs) para la determinación del sudor en la monitorización deportiva. Objetivos: Desarrollar un sensor con sustrato GCE recubierto de Ag NPs/SPCE. Métodos: Se utilizó el análisis FESEM y XRD para las caracterizaciones morfológicas y estructurales de las NPs de Ag y SPCE, respectivamente. Resultados: Los resultados de FESEM, EDS y XRD revelaron que las NPs de Ag estaban uniformemente dispersas en el SPCE. El biosensor electroquímico respondió linealmente al lactato en soluciones de tampón fosfato, con límites de detección y sensibilidad de 1,2 µM y 14,2 mAcm-2 mM-1, respectivamente. Conclusión: Los resultados sugieren que Ag NPs/SPCE puede utilizarse para monitorizar de forma continua los niveles de lactato en el sudor como un biosensor práctico y fiable para su uso. Nivel de evidencia II; Estudios terapéuticos - investigación de los resultados del tratamiento.

Analysis and Research on Sustainable Development Factors of the Sports Industry Based on Chaos Theory.

The sports industry is an emerging industry with broad development prospects, and it is also full of competition. The sports industry has the characteristics of fluctuation, intermittence, and randomness, which are suitable for the analysis of chaos theory in order to find out the internal development law of the sports industry. In order to solve the above problems, an improved chaos theory method is proposed in this paper and the K-cluster analysis method is integrated into chaos calculation, in order to reduce the occurrence rate of the "local extreme value" and improve the accuracy of calculation results. The model uses nonlinear and irregular chaos theory to analyze the aggregation degree of sports industry, industrial spatial distribution, and the spatial governance effect and find out the best optimization decision. When selecting the optimization indicators, not only the European distance of each indicator cluster but also the spatial correlation of the indicators are considered to realize the comprehensive analysis of the sports industry and improve the accuracy of optimization. In the simulation analysis of optimization decision-making, the decision-making model based on chaos theory is compared with the previous first-order decision-making model. The results show that the improved chaos theory can control the data aggregation range of sports industry between (0∼3), the data fusion degree of industrial space between 95 and 99%, and the variation range between 0 and 0.2%, which is significantly better than (0∼9), 90∼95%, and 0∼0.4% of the genetic algorithm. Therefore, the aggregation degree, spatial governance, and decision optimization of the optimization decision-making model proposed in this paper are better than those of the previous genetic algorithm.