Broad Applications of Consumer-Grade Eeg Devices: From Clinical Diagnostics to Brain-Computer Interfaces and Social Sciences – Literature Review

Research Objective: This review article aims to assess the rapidly growing market for commercial electroencephalography (EEG) devices and analyze their transition from sterile laboratory conditions to a variety of real-world applications. The paper examines the technological evolution of wireless systems and their effectiveness in clinical, social, and engineering fields. Methods: This article synthesizes the current scientific literature on mobile EEG platforms, such as the Emotiv and Muse systems, and Ear-EEG technologies. Applications are classified by clinical specialties, behavioral monitoring, and novel brain-computer interface (BCI) technologies, while also assessing validation studies against the "gold standard" of medical equipment. Results: The analysis demonstrates that modern consumer-grade EEG devices, supported by machine learning algorithms and artificial intelligence, provide high diagnostic accuracy in detecting sleep disorders, neurodegenerative markers (Alzheimer's and Parkinson's disease), and psychiatric conditions (anxiety, depression, ADHD). Furthermore, the review identifies key advances in emergency neurology, addiction monitoring, and intraoperative safety. Emerging fields such as ethical neuromarketing and BCI-guided assistive robotics demonstrate the technology's potential to improve human-machine interaction and social inclusion for people with disabilities. Conclusions: Commercial EEG devices represent a paradigm shift in personalized healthcare and social science research. Despite persistent challenges related to signal artifacts and data privacy, the democratization of neurotechnology enables continuous monitoring with high ecological validity. Integrating these devices into everyday life offers unprecedented opportunities for early diagnosis, non-pharmacological interventions, and the development of "digital biomarkers” ultimately transforming brain health management and decision-making in the digital age.