Abstract

AbstractUrine Specific Gravity (USG) is a direct indicator of the osmolarity of the urine and therefore it can be considered as a nonspecific marker of several underlying diseases which result in changes in hydration levels of the body. Here, a biosensor based on the principle of localized surface plasmon resonance (LSPR) is developed, which utilizes its refractive index sensing properties to measure USG with a sensitivity of 79.21 nm USG−1unit. Additionally, the sensor can measure the serum protein content within the urine. Traditionally, handheld refractometers are used to measure USG which are operated as calibrated refractive index scales rather than a sensor. A simple experiment demonstrating the advantage of a sensor over scale, with LSPR as the transduction method, is also conducted to highlight the enhanced sensitivity of a sensor over a scale. Finally, analysis of results with an unsupervised machine learning algorithm, principal component analysis (PCA), demonstrate the feasibility of automating or perhaps adding artificial intelligence to such sensors, thereby exemplifying a potential paradigm shift from refractive index scales to sensors in USG measurement.

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