Fecal gas time curve analysis for health monitoring.

Abstract

Human feces are metabolic waste products that emit a wide range of volatile organic compounds, the result of dynamic interactions between gut microbiota and the host physiology. Fecal gas profiles are recognized as potential indicators of an individual's health status; however, most analyses rely on expensive laboratory equipment such as gas chromatography. In contrast, studies utilizing low-cost gas sensors for stool gas analysis remain limited, partly due to the high sensitivity of gas concentration data to environmental variables such as stool weight and ambient conditions. In this study, gas concentration data (ppm) were converted into normalized gas reduction ratio curves (%), referred to here as time curves, so that temporal gas-release patterns could be compared across samples with reduced influence from absolute signal differences. Fifteen stool samples were collected from four individuals and analyzed according to the Bristol stool scale. Time curves corresponding to the same Bristol stool type showed reproducible convergence into representative temporal profiles, where different stool types exhibited distinguishable gas-decay patterns. These findings suggest that time curve analysis may be useful for characterizing stool-type-related temporal gas patterns while reducing the influence of environmental variability in low-cost fecal gas sensing.