EEG-Enabled Digital Health: AI, Wearables, Biomarkers, and Secure Clinical Applications

Electroencephalography is increasingly moving beyond specialist laboratories into wearable devices, home-based monitoring systems and digitally connected care environments. Advances in portable EEG, artificial intelligence, digital biomarkers, cloud and edge computing are creating new opportunities for continuous brain-health monitoring and personalized management of neurological, psychiatric, cognitive and sleep-related conditions. However, challenges related to signal quality, clinical validation, interoperability, explainability, usability, privacy, cybersecurity and responsible integration into healthcare workflows continue to limit widespread adoption.Successful EEG-enabled digital-health applications require more than accurate signal classification; they must also be clinically meaningful, understandable, accessible, secure and suitable for real-world healthcare environments. This Research Topic aims to bring together researchers, clinicians, engineers, behavioral scientists, health informatics specialists and implementation experts to address the complete pathway from EEG data collection and analysis to patient communication, personalized intervention, clinical adoption and responsible implementation. It will particularly encourage research addressing usability, trust, privacy, fairness, health literacy and the ethical management of sensitive brain data.Suitable themes for manuscripts include (but are not limited to):• Connected and remote EEG monitoring for home, community and clinical care.• Wearable, portable, dry-electrode and in-ear EEG technologies.• EEG-based digital biomarkers for neurological, mental-health, cognitive and sleep-related conditions.• Artificial intelligence, machine learning, deep learning and graph-based EEG analysis.• Explainable and clinically interpretable EEG decision-support systems.• Multimodal digital-health systems integrating EEG with physiological, behavioral, speech, imaging and wearable-sensor data.• Health informatics platforms integrating EEG with electronic health records, mobile-health applications and telehealth systems.• Personalized prediction, treatment selection, rehabilitation, neurofeedback and adaptive digital interventions.• Clinical validation, human-centered design, usability and real-world implementation of EEG-enabled technologies.• Privacy, cybersecurity, informed consent, algorithmic fairness, governance and responsible use of brain data. Topic editors: Supriya Supriya, Siuly Siuly Source: https://www.frontiersin.org/research-topics/83969/eeg-enabled-digital-health-ai-wearables-biomarkers-and-secure-clinical-applications