Investigation of the Effect of Building Facades on Brain Signals by EEG Analysis Method 

The human mind creates a perception about space by evaluating the facade with visual cues. Visual stimuli located on the front cause complex neural activations in the human brain. These activations can be measured with neurophysiological devices such as electroencephalogram (EEG). In the study; it was aimed to determine the different emotional states caused by visual stimuli and to classify these emotions with EEG signals. The mentioned classification method; It was tested on the facades of 3 different building samples selected from Mastfroş street, a region where there are new buildings in Diyarbakır, from the Huzurevleri area where building facades are aging and deformed, and from the Kıtılbil neighborhood where there is a villa-type construction. As a method in the study; the collection of EEG data, data preprocessing, artificial intelligence-based analysis, classification and interpretation of results steps are included. For classification, artificial neural networks (ANNs), which were developed inspired by the functioning of biological neural networks and have the ability to process and learn information, were used. Powerful models are needed for the analysis of complex data sets in machine learning. In these models, the Multi-Layer Perceptron (MLP) Classification method, which is used to classify complex data sets by creating nonlinear decision boundaries, has been applied. Using this method; as a result of the study, the effect of facades on human perception was proved with quantitative data. Thus, the abstract perceptual effects of building facades were evaluated based on concrete data obtained using artificial intelligence-based analysis and classification methods.