# Advancements in EEG Emotion Recognition: Leveraging Multi-Modal Database Integration
## 3 Multi-Modal System EEG with Facial Expressions--Proposed Model
### EEG Topographies and Brain Heat Maps  
The characterization of EEG signal shape is dependent on demonstrating brain activity at the moment of capturing the waveform, which is dependent on the brain region that is active at that particular time. The human brain has three major lobes. The cerebrum, the largest in size and most vital human brain segment, is divided into two hemispheres,each housing four distinct lobes: frontal, parietal, temporal, and occipital. The frontal lobe governs complex voluntary motions and influences judgment, personality, decision-making, and cognitive functions like abstract thought, language, and problem-solving. Processing somatosensory details, the parietal lobe handles touch sensation and movement coordination [50]. The temporal lobe manages auditory input, memory processing, and speech functions, while the smallest lobe, the occipital lobe, oversees vision, including color perception and spatial awareness. The brainstem controls vital life activities such as breathing, blood pressure regulation, and swallowing. Finally, the cerebellum is in charge of maintaining balance and precisely coordinating motions like walking and speech. EEG waves have diverse shapes that indicate different types of brain activity [51]. The EEG signal is usually shown and presented as a chronological sequence of voltage values, reflecting the electrical activity detected by electrodes and measured in microvolts (\(\mathrm{\SIUnitSymbolMicro V}\)). This signal is regularly sampled at consistent intervals, typically falling within the range of 128 Hz to 1024 Hz. Standard EEG signals encompass a frequency spectrum of up to 45 Hz, but in unique situations, this range may extend beyond 200 Hz. Conventionally, theses are categorized into specific frequency bands: delta, theta, alpha, beta, and gamma waves. These EEG frequencies represent various electrical activities within the brain and offer insights into the functioning of different brain regions, as established by [PERSON]. [52]. The utilization of EEG frequencies is widespread in the monitoring of brain activity during various activities such as relaxation, sleep, and meditation, as well as in the diagnosis and treatment of numerous neurological and psychiatric conditions [53]. For instance, deep sleep is characterized by higher signal power in the delta band, signifying specific brain activity during this sleep stage. Theta, alpha, and beta bands have empirically demonstrated interest in emotion identification, as documented in publications [33; 54; 55]. Unwanted frequency bands are filtered out using a second-order bandpass filter. EEG topography stands as a non-invasive technique enabling researchers to create a real-time visual representation of the electrical activity within the brain. This method has found widespread application in neuroscience, facilitating the exploration of various facets of brain function, encompassing cognition, emotion, and perception. The EEG and brain heat map representation, called EEG topography, is shown in Figure 6. These topographies might look clearly different when there is a change in the set of electrodes, frequency ranges, or the window time frame used to build up the 2D map. In this study, each 1 s time frame is considered to be a single topography without overlap. Window size helps in reducing the noise to avoid problems that occur due to the continuous huge and fast changes in human brain signals. EEG signals are not stable since they are affected by every movement, thought, emotion, or feeling. Figure 6: An example of an EEG 2D topography. The raw EEG data undergo analysis and processing to generate a brain activity heat map, showing the distribution of human brain signals as electrical activity all over the scalp using different electrodes placed in different locations. This technique has proven invaluable in unraveling the neural mechanisms that underlie behavior and cognition, establishing itself as an essential tool for researchers in neuroscience.