A Novel Acetone Sensor for Body Fluids

Population growth and urban lifestyles have contributed to the increased consumption of industrialized fast food, while sedentary behaviors have fostered metabolic disorders, ultimately leading to premature mortality. Changes in body weight and associated conditions, such as obesity, diabetes, and other related pathologies, necessitate monitoring metabolic changes through biomarkers that effectively indicate health risks. Ketones are established biomarkers of fat oxidation, produced in the liver as a byproduct of lipolysis. They include acetoacetic acid and hydroxybutyric acid in the blood and acetone in our breath and skin. Monitoring ketone production in the body is essential for people who use caloric intake deficit to reduce body weight or use ketogenic diets for wellness or treatments. Current ketone monitoring methods include urine dipsticks, capillary blood monitors, and breath analyzers. However, these existing methods have limitations that hinder their broader application. This work presents the development of a novel acetone sensor designed to detect breath and skin acetone and address the limitations of existing sensing methods. The key component of this sensor is a robust pH-indicator sensing solution capable of measuring acetone using a complementary metal oxide semiconductor (CMOS) chip, coupled with efficient data analysis via a red, green, and blue deconvolution imaging approach. The acetone sensor demonstrated sensitivity in the micromolar concentration range, selectivity for acetone detection in breath, and a stable operational lifetime of at least one month. The sensor’s performance was validated through a human breath sample test using a well-established blood ketone reference method. In addition, a second approach developed in this work was the synthesis and use of the liquid-cored microsphere containing a hydroxylamine/thymol blue sensing probe. Sensors utilizing liquid-core microspheres and polyvinyl alcohol as binding agents were fabricated on a transparent polyethylene terephthalate (PET) substrate and calibrated using simulated breath and skin acetone samples. Furthermore, a custom signal processing algorithm was developed to process sensor signals, enabling the simulation of real-time, continuous monitoring of skin acetone levels. This is the first instance of a colorimetric detection mechanism, allowing continuous measurement of skin acetone. Finally, a fat oxidation model incorporating ketone metrics was developed and correlated with skin acetone levels, establishing a direct link to body fat burning and offering a means to report clinically meaningful personal results for future integration into actionable insights in behavioral health.