Modeling surface conductivity in a sweat analyzing wearable smart textile platform

Abstract

Wearable self-health monitoring devices are a contemporary necessity with modern life-style and health implications of this decade. Current devices have transitioned to non-invasive sampling due to benefits including minimal possibility of infections, convenience, no requirement for storage, and physiological safety of neo-natal and geriatric patients. Sweat, in this regard, is of importance as the variations in the sweat composition have been validated as bio markers of different diseases. Corresponding variations in the surface resistivity as the sweat composition is changed, has been introduced in this novel research with a synergistic approach, based on developing a conductive sweat sensing and analyzing textile platform. The relationship between the macro porosity of the proposed textile platform and the measured surface conductivity values has been mathematically modeled and presented in this paper. A simulation of the mathematical model concluded that variations in the localized surface area for sweat accumulation and the fabric weight of the textile platform has minimal effect on the performance of the wearable sweat monitoring platform, while a satisfactorily measurable surface conductivity value can be obtained at sweat concentration levels in the order 0.01M.