Cortisol hormone and stress levels: colorimetric assessment with artificial intelligence supported image processing method

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dc.contributor.authorCingöz Çapan, Ebru
dc.contributor.authorÇapan, Muhammed Ertuğrul
dc.contributor.authorÖncel, Hasan Uğur
dc.contributor.authorArıcan, Ercan
dc.date.accessioned2026-03-16T06:08:50Z
dc.date.available2026-03-16T06:08:50Z
dc.date.issued2026
dc.departmentFakülteler, Sağlık Bilimleri Fakültesi, Fizyoterapi ve Rehabilitasyon Bölümü
dc.description.abstractThis study presents a new method for determining cortisol hormone levels, a key biomarker of stress, using microfluidic pads to collect sweat samples. The pads facilitate the colorimetric detection of cortisol levels via the blue tetrazolium method. The resulting color change is analytically assessed using Convolutional Neural Networks (CNN), Decision Trees, and Vector Regression, alongside advanced image processing techniques. The developed algorithm is robust, providing reliable results despite hardware variations and color distortion, enhancing the system's applicability and generalizability across different environments. Validation studies conducted with ELISA and a colorimeter revealed that the system achieved an accuracy of 84.2% in determining users' cortisol levels. Additionally, psychosocial stress levels were assessed using the Copenhagen Psychosocial Risk Assessment and the Perceived Stress Scale tests during the collection of sweat samples from 20 participants. The results demonstrated a significant correlation between cortisol levels and stress, confirming the method's reliability and effectiveness in various applications.
dc.description.sponsorshipIstanbul University ; FYL-2022-38254
dc.identifier.doi10.36306/konjes.1633932
dc.identifier.issn2667-8055
dc.identifier.issue1
dc.identifier.urihttps://doi.org/10.36306/konjes.1633932
dc.identifier.urihttps://hdl.handle.net/11501/2662
dc.identifier.volume14
dc.identifier.wosWOS:001705363600006
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.institutionauthorÖncel, Hasan Uğur
dc.institutionauthorid0000-0002-6900-1955
dc.language.isoen
dc.publisherKonya Teknik University
dc.relation.ispartofKonya Journal of Engineering Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectComputer Vision
dc.subjectConvolutional Neural Networks
dc.subjectCortisol Hormone
dc.subjectOccupational Stress
dc.subjectPsychosocial Risk Assessment
dc.titleCortisol hormone and stress levels: colorimetric assessment with artificial intelligence supported image processing method
dc.typeArticle

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