Predicting Architectural Space Preferences Using EEG-Based Emotion Analysis: A CNN-LSTM Approach

Architectural elements—such as shapes, colors, and lighting—significantly influence how users emotionally respond to spaces. This study addresses the challenge of capturing unconscious and rapid emotional responses by employing a 32-channel electroencephalography (EEG) approach with 40 participants,...

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Hlavní autoři:	Ju Eun Cho, Se Yeon Kang, Yi Yeon Hong, Han Jong Jun
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2025-04-01
Edice:	Applied Sciences
Témata:	EEG event-related potential convolutional neural network long short-term memory affective architecture user preference prediction
On-line přístup:	https://www.mdpi.com/2076-3417/15/8/4217
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