RESUMEN
With the popularization of the Internet of Things, the application of chemical sensors has become more and more extensive. However, it is difficult for a single functional sensor to meet multiple needs at the same time. For the next generation of chemical sensors, in addition to rapid qualitative and quantitative detection, it is also necessary to solve the problem of a distributed sensor power supply. Triboelectric nanogenerator (TENG) and surface-enhanced Raman scattering (SERS) are two emerging technologies that can be used for chemical testing. The combination of TENG and SERS technology is proposed to be an attractive research strategy to implement qualitative and quantitative analysis, as well as self-powered detection in one device. Herein, the Ag nanoparticle (NP)@polydimethylsiloxane (PDMS) plasmonic cavity is demonstrated, which can be exploited not only as a SERS substrate for qualitative analysis of the target molecules but also as a TENG based self-powered chemical sensor for rapid quantitative analysis. More importantly, the as-designed plasmonic cavity enables prolonged triboelectric field generated by the phenomena of triboelectricity, which in turn enhances the "hot spot" intensities from Ag NPs in the cavity and boosts the SERS signals. In this way, the device can have good feasibility and versatility for chemical detection. Specifically, the measurement of the concentration of many analytes can be successfully realized, including ions and small molecules. The results verify that the proposed sensor system has the potential for self-powered chemical sensors for environmental monitoring and analytical chemistry.
RESUMEN
Diabetic foot is one of the main complications of diabetes with the characteristics of high incidence and difficulty in treatment. Diabetic patients with peripheral neuropathy may develop foot ulcers, and in severe cases amputations are required and some may even die. Plantar pressure can be used to assess the risk of developing diabetic foot, but the existing plantar pressure monitoring methods are not suitable for long-term monitoring in daily life. This study presents a novel low-cost shoe system for daily monitoring of plantar pressure in diabetics. It includes an insole with pressure sensor array, which can dynamically monitor the plantar pressure and display the changes of plantar pressure in real time in the mobile phone to provide early warning for patients with high risk of diabetic foot. As for the sensor, copper and carbon black were adopted as the electrode and conductive filler respectively, enabling a mass production with low price. It was soft and bendable, meeting the performance needs of daily plantar pressure monitoring. All devices were encapsulated in shoes, and the data was transmitted wirelessly through Bluetooth, which did not affect the user's walking. After using random forest for feature selection, five classifiers were used to classify the plantar pressure of healthy people, diabetic patients without peripheral neuropathy, and diabetic patients with peripheral neuropathy collected by this system. The experimental results showed that the accuracy of the random forest classifier was the highest, reaching 94.7%, which indicated that the system could be useful for daily plantar pressure monitoring of diabetic patients.