# Predicting Architectural Space Preferences Using EEG-Based Emotion Analysis: A CNN-LSTM Approach
## 2 Literature Review
### Theoretical Background of EEG-Based Emotion Analysis  
\"EEG\" is a noninvasive method for measuring the brain's electrical activity in real time through electrodes placed on the scalp [23]. It offers a high temporal resolution on the scale of milliseconds, capturing momentary emotional and cognitive processes. EEG signals span multiple frequency bands, from delta (0.5-4 Hz) to gamma (30-100 Hz or higher), each reflecting various cognitive states [24; 25]. Because of these features, EEG is widely applied in fields such as learning, decision-making, and emotion recognition. Among EEG-based methods, ERP analysis focuses on time-locking the EEG signal to the onset of specific stimuli, thereby isolating and quantifying the brain's rapid responses to those stimuli [26]. By observing ERP components such as N100, N200, P300, and LPP following spatial stimuli, one can quantitatively infer how users perceive and evaluate those stimuli [27]. EEG data can be analyzed from different perspectives--time, frequency, or spatial domain--as summarized in Table 2. For instance, a time-domain analysis is well suited for \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Architectural Element** & **Characteristic** & **Emotional Effect** & **Preference Effect** \\ \cline{2-4}  & Curved & Provides psychological stability & Increases positive evaluation \\ \cline{2-4} Spatial form [15; 16; 17; 18; 19; 20] & Excessive curves & Can cause stress & Reduces preference \\ \cline{2-4}  & Straight lines & Conveys an efficient and organized impression & Preferred in certain contexts \\ \hline \multirow{2}{*}{Lighting [21]} & Natural lighting & Relieves stress and fosters positive emotions & Increases preference \\ \cline{2-4}  & Artificial lighting & May create emotional distance & Sometimes lowers preference \\ \hline \multirow{2}{*}{Ceiling height [22]} & High ceiling & Engenders openness and creativity & Enhances space preference \\ \cline{2-4}  & Low ceiling & Promotes concentration & Preferred for certain tasks \\ \hline \multirow{2}{*}{Color [14; 15]} & Warm tones & Provide psychological comfort & Boost preference generally \\ \cline{2-4}  & Cool tones & Convey a sense of distance & Preference depends on context \\ \hline \multirow{2}{*}{Materials [14]} & Natural materials & Impart warmth and stability & Yield a higher preference \\ \cline{2-4}  & Artificial materials & Create emotional distance & Tend to lower preference \\ \hline \multirow{2}{*}{Sound [14; 22]} & Proper acoustic & \multirow{2}{*}{Offers a comfortable, stable atmosphere} & Improves user experience \\ \cline{1-1}  & design & & \\ \cline{1-1} \cline{2-4}  & Excessive noise & Generates unpleasant feelings & Decreases preference \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Key architectural elements and their emotional and preference effects. ERP assessments, while a frequency-domain analysis uses specific bands (e.g., alpha and beta) to gauge the cognitive load or emotional state [28; 29; 30; 31; 32; 33; 34; 35; 36]. Because EEG provides real-time emotional analysis and more objective data than self-reported measures, its potential has been recognized in diverse applications such as human-computer interactions and brain-computer interfaces [52; 53]. For instance, EEG in gaming or VR environments can detect real-time changes in user state, adjusting interfaces  
\begin{table}
\begin{tabular}{c c c c} \hline