Determination of Cortisol Hormone from Sweat Samples and Interpretation with Microcontroller

Yıl 2024, Cilt: 13 Sayı: 3, 646 - 658, 26.09.2024

Muhammed Ertuğrul Çapan , Ebru Cingöz , Hasan Uğur Öncel , Ercan Arıcan

https://doi.org/10.17798/bitlisfen.1470481

Öz

Cortisol, known as the body's stress hormone, regulates metabolism, inflammation, and the immune system. It affects various bodily systems such as the nervous, immune, cardiovascular, respiratory, reproductive, and musculoskeletal systems. Normal sweat cortisol levels range from 8 to 142 ng/ml, with elevated levels indicating stress (200 ng/ml in women, 500 ng/ml in men).

This study focuses on colorimetric cortisol analysis using a microfluidic layer to collect sweat samples. Samples are mixed with a specific color reagent. Cortisol levels are quantitatively analyzed using Z-Score values and RGB channel density via photographs taken with the ESP 32 module. The aim is to determine cortisol levels, aiding in diagnosing conditions like Cushing's syndrome and Addison's Disease, leveraging wearable technology.

The developed system integrates a microcontroller into the wearable microfluidic system for cortisol measurements throughout the day. Data is displayed and recorded on a computer for streamlined cortisol monitoring.

The blue tetrazolium method used offers stable colors and rapid reactions (10 minutes). The Limit of Detection (LOD) is 0.3 ug/mL, with a detection limit of 1.1 ug/mL. Combined with the ESP 32 Cam module, the system detects cortisol concentrations from 0.8 – 60 ug/mL.

Anahtar Kelimeler

Microfluidic, Cortisol Hormone, Microcontrollers, Colorimetirc Analaysis

Etik Beyan

"The prepared article does not require ethical approval." "The prepared article does not have any conflict of interest with any individual/institution."

Destekleyen Kurum

This study was supported within the scope of ISTANBUL GEDIK University BAP Graduate Thesis Project numbered BAP.FR.25. This study was supported within the scope of ISTANBUL University BAP Graduate Thesis Project numbered FYL-2022-38254 Project Id 38254.

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