MATHEMATICAL MODELLING OF STRESS HORMONE DYNAMICS INVOLVING LEVELS OF DAILY MOOD

• Main Author: Nur'aini Muthmainnah, Luthfia
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/76393
• Institution: Institut Teknologi Bandung

Technological developments make several changes in human life, including communication and accessing information. This has led to an increased opportunity for individuals to compare their achievements or accomplishments with each other, which over time can trigger a habit of constantly comparing themselves to others. This behavior can eventually lead to stress in individuals. The factors that trigger stress are known as stressors. Stress is a psychological response when faced with challenging situations. In this final project, the growth of stressors is represented by the value of the growth rate constant kc. The response to this stress can vary, including excessive worrying and heightened attention to detail when working on tasks. In the human body, there is a stress response mechanism in the hypothalamus that involves three major hormones: Corticotropin-releasing hormone (CRH), Adrenocorticotropic hormone (ACTH), and cortisol. When responding to stress, these three hormones increase until their levels are sufficient to manage the stressor. Thus, there is a suppression of hormone levels described by a negative feedback response mechanism. This mechanism is modeled using a modified Michaelis- Menten equation to illustrate the inhibition of the stressor growth rate. This process is simulated by varying initial conditions to observe hormone dynamics under different circumstances. To examine the dynamics of cortisol hormone, a survey was conducted to gather information on the dynamics of feelings and levels of stressors among individuals with different characteristics. To understand the emotional dynamics, an adapted equation of a mass-spring system with an external disturbance function was used. From the obtained function, the movement and individual responses to stressors were analyzed. Subsequently, simulations were conducted using a system of linear equations with the value of kc obtained from the survey data processing.