Rethinking human perception of indoor thermal environments: an ElectroEncephaloGram (EEG) approach

This thesis explores how people’s brains respond to indoor thermal environments using EEG, a method that records brain activity. It shows how brain signals can tell us whether someone feels warm, cool, or neutral. It also reveals how people adapt to thermal environmental changes and how they react to pleasant or unpleasant shifts. The study tests how different thermal factors affect the brain and uses machine learning to identify patterns. It finds reliable brain signatures that reflect thermal comfort. These findings support the design of smart indoor environments that adapt to how people feel, improving comfort, health, and energy efficiency.