An automatic cortisol measurement device based on 3D printing and image processing

Abstract

Depression has become a pervasive mental health issue, affecting millions of people worldwide. According to the World Health Organization, more than 264 million people suffer from depression globally, making it a leading cause of disability and contributing significantly to the overall burden of disease. Cortisol, a steroid hormone released in response to stress, has been closely linked to depression. Elevated cortisol levels are often observed in individuals with major depressive disorder (MDD), and dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is considered a hallmark of depression. Therefore, monitoring cortisol levels can provide valuable insights into the severity and progression of depression, aiding in both diagnosis and treatment. Despite the importance of cortisol measurement, current methods such as enzyme-linked immunosorbent assays (ELISA) and liquid chromatography-mass spectrometry (LC-MS) are often impractical for routine monitoring due to their high cost, complexity, and the need for specialized equipment and personnel. This underscores the necessity for portable, accurate, and user-friendly cortisol measurement devices that can be used in various settings, including clinical environments and home monitoring. This dissertation focuses on the development of a portable cortisol measurement device using advanced 3D modeling and printing techniques, PCB design and control, and image processing methods. The hardware design is based on Fusion 360 from Autodesk, which is used to implement 3D modeling and printing of the device. For the electronic components, a custom PCB was developed using Python and a Linux-based system, ensuring accurate control of LED and camera module. Finally, image processing techniques, such as color space conversion and thresholding, are employed to accurately analyze the test strips and provide quantitative results. This combination of advanced modeling, precise hardware development, and sophisticated image processing enables a reliable and user-friendly cortisol measurement solution, essential for effective depression diagnosis and management.