Recent Progress in In-Ear EEG Technology and Its Emerging Real-World Applications: A Review

Area of Science:

• Neuroscience and Biomedical Engineering
• Wearable Technology
• Signal Processing

Background:

• Conventional Electroencephalography (EEG) systems face challenges in setup complexity and portability.
• Ear-based EEG (ear EEG) technology, particularly in-ear types, offers a compact and wearable alternative for brain activity monitoring.
• Current in-ear EEG research is primarily focused on feasibility and small-scale studies, lacking systematic integration of personalized design and advanced signal processing.

Purpose of the Study:

• To review recent advancements in ear EEG systems, with a focus on in-ear configurations.
• To summarize key achievements in hardware design, including structural innovation and material development.
• To analyze the applications of in-ear EEG in brain-computer interfaces (BCI) and brain state monitoring.

Main Methods:

• Review of the latest research on in-ear EEG systems, focusing on hardware innovations (structure, materials).
• Summary of typical applications in brain-computer interfaces (BCI), including steady-state responses, event-related potentials, and motor imagery.
• Analysis of in-ear EEG applications in brain state monitoring, such as sleep tracking, epilepsy detection, drowsiness evaluation, and emotion recognition.

Main Results:

• Significant progress has been made in the hardware design of in-ear EEG systems through structural and material innovations.
• In-ear EEG has demonstrated potential in various BCI applications and for monitoring brain states like sleep, epilepsy, drowsiness, and emotions.
• Key limitations hindering clinical translation include the lack of personalized design integration and systematic signal processing, alongside the absence of multi-center clinical trials.

Conclusions:

• In-ear EEG technology presents a promising, portable solution for brain activity monitoring and BCI applications.
• Addressing current bottlenecks, such as personalized design, intelligent signal processing, and multi-center trials, is crucial for clinical transformation.
• This review provides a foundational framework and identifies critical research directions for the advancement of in-ear EEG systems.