Mihai Ungureanu Alexandra Stefania, Geman Oana, Toderean Roxana, Miron Lucas, SharghiLavan Sara
Computers, Electronics and Automation Department, Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, 720229 Suceava, Romania.
Data Science and AI Group, Department of Computer Science Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden.
Sensors (Basel). 2025 May 25;25(11):3321. doi: 10.3390/s25113321.
Electroencephalography (EEG) remains an essential method for monitoring brain activity, but the limitations of conventional systems due to the complexity of installation and lack of portability have led to the introduction and development of in-ear EEG technology. In-ear EEG is an emerging method of recording electrical activity in the brain and is an innovative concept that offers multiple advantages both from the point of view of the device itself, which is easily portable, and from the user's point of view, who is more comfortable with it, even in long-term use. One of the fundamental components of this type of device is the electrodes used to capture the EEG signal. This innovative method allows bioelectrical signals to be captured through electrodes integrated into an earpiece, offering significant advantages in terms of comfort, portability, and accessibility. Recent studies have demonstrated that in-ear EEG can record signals qualitatively comparable to scalp EEG, with an optimized signal-to-noise ratio and improved electrode stability. Furthermore, this review provides a comparative synthesis of performance parameters such as signal-to-noise ratio (SNR), common-mode rejection ratio (CMRR), signal amplitude, and comfort, highlighting the strengths and limitations of in-ear EEG systems relative to conventional scalp EEG. This study also introduces a visual model outlining the stages of technological development for in-ear EEG, from initial research to clinical and commercial deployment. Particular attention is given to current innovations in electrode materials and design strategies aimed at balancing biocompatibility, signal fidelity, and anatomical adaptability. This article analyzes the evolution of EEG in the ear, briefly presents the comparative aspects of EEG-EEG in the ear from the perspective of the electrodes used, highlighting the advantages and challenges of using this new technology. It also discusses aspects related to the electrodes used in EEG in the ear: types of electrodes used in EEG in the ear, improvement of contact impedance, and adaptability to the anatomical variability of the ear canal. A comparative analysis of electrode performance in terms of signal quality, long-term stability, and compatibility with use in daily life was also performed. The integration of intra-auricular EEG in wearable devices opens new perspectives for clinical applications, including sleep monitoring, epilepsy diagnosis, and brain-computer interfaces. This study highlights the challenges and prospects in the development of in-ear EEG electrodes, with a focus on integration into wearable devices and the use of biocompatible materials to improve durability and enhance user comfort. Despite its considerable potential, the widespread deployment of in-ear EEG faces challenges such as anatomical variability of the ear canal, optimization of ergonomics, and reduction in motion artifacts. Future research aims to improve device design for long-term monitoring, integrate advanced signal processing algorithms, and explore applications in neurorehabilitation and early diagnosis of neurodegenerative diseases.
脑电图(EEG)仍然是监测大脑活动的重要方法,但传统系统由于安装复杂和缺乏便携性的局限性,促使了入耳式脑电图技术的引入和发展。入耳式脑电图是一种新兴的记录大脑电活动的方法,从设备本身易于携带的角度以及用户即使长期使用也更舒适的角度来看,这是一个具有多种优势的创新概念。这类设备的一个基本组件是用于捕捉脑电图信号的电极。这种创新方法允许通过集成在耳机中的电极捕捉生物电信号,在舒适度、便携性和可及性方面具有显著优势。最近的研究表明,入耳式脑电图能够记录与头皮脑电图质量相当的信号,具有优化的信噪比和改善的电极稳定性。此外,本综述对诸如信噪比(SNR)、共模抑制比(CMRR)、信号幅度和舒适度等性能参数进行了比较综合,突出了入耳式脑电图系统相对于传统头皮脑电图的优势和局限性。本研究还引入了一个可视化模型,概述了入耳式脑电图从初始研究到临床和商业应用的技术发展阶段。特别关注了电极材料和设计策略方面的当前创新,旨在平衡生物相容性、信号保真度和解剖适应性。本文分析了入耳式脑电图的发展历程,从所使用电极的角度简要介绍了入耳式脑电图的比较方面,突出了使用这项新技术的优势和挑战。还讨论了与入耳式脑电图中使用的电极相关的方面:入耳式脑电图中使用的电极类型、接触阻抗的改善以及对耳道解剖变异性的适应性。还对电极在信号质量、长期稳定性以及与日常生活使用的兼容性方面的性能进行了比较分析。将耳内脑电图集成到可穿戴设备中为临床应用开辟了新的前景,包括睡眠监测、癫痫诊断和脑机接口。本研究突出了入耳式脑电图电极开发中的挑战和前景,重点是集成到可穿戴设备中以及使用生物相容性材料来提高耐用性并增强用户舒适度。尽管入耳式脑电图具有巨大潜力,但其广泛应用面临诸如耳道解剖变异性、人体工程学优化和减少运动伪影等挑战。未来的研究旨在改进用于长期监测的设备设计,集成先进的信号处理算法,并探索在神经康复和神经退行性疾病早期诊断中的应用。