A Comprehensive Review of Modern EEG Signal Processing for Emotional and Stress Detection: From Data to Insight

Abstract

Using the brain's thoughts to communicate with the outside world is known as brain-computer interface. Electroencephalography (EEG) has emerged as a powerful non-invasive method for understanding brain activity and developing applications in neurology, medicine, and human-computer interaction.

Robust signal processing techniques, which convert raw EEG data into meaningful insights, are crucial to the effectiveness of EEG-based systems. This paper aimed to discuss the various approaches that need to be adjusted for each stage of brain signal processing, with a number of approaches and experimental results reported and compared in previous surveys. The advantages and disadvantages of each method, such as signal capture, signal augmentation, feature extraction, and signal classification, are easily and clearly interpreted in this work.