Exploration of Impactful Brain Region and EEG Bands for Affective Computing**

Millions of neurons in the human brain are essential for controlling how the body reacts to internal and external motor impulses. These neurons contain emotional encoding as well. Electroencephalography (EEG) is a potent tool for recording brain waves associated with different states of the scalp surface. Different signal categories are defined using signal frequencies spanning the delta, theta, alpha, beta, and gamma ranges from 0.1 Hz to over 100 Hz. EEG-based brain-computer interfaces (BCI) have permitted the rapid expansion of the field of emotion recognition for many real-life applications. This research explores the impactful brain regions and EEG bands for affective computing. A comparative examination of various algorithms using various regions and bands is performed. In this work, the discrete wavelet transform (DWT) is used to separate EEG signals into several frequency bands associated with EEG bands. The experiments are conducted on a publicly available DEAP dataset. The DWT is applied to each participant for each EEG channel to identify potent brain regions and EEG bands for emotional computing. This work's outcomes improve the dynamic computing field and open new avenues for research into the complex interplay between brain activity and emotions.