Materials and Structures of Skin-Interfaced Electrodes for Reducing Motion Artifacts in Neural Recording

Motion artifacts are a primary obstacle to reliable electrophysiological signal acquisition when employing electroencephalography (EEG) using skin-interfaced electrodes. Although filtering algorithms commonly remove such signal disturbances, advanced electrode materials that physically reduce interface noise have emerged as more effective solutions. This review summarizes recent advances in the materials and structures of neural interface electrodes for the longitudinal and stable monitoring of EEG signals. The developments are examined across two architectural paradigms: thin-film electrodes utilizing material thinning for conformal contact and bulk-patch electrodes employing 3D matrices with tissue-like properties. Thin-film designs include metal and 2D material-based systems, hybrid composites, and porous architectures. Bulk-patch electrodes address five key domains: adhesion mechanisms, sol-gel transitions, moisture adaptability, self-healing networks, and frequency-selective damping. Recent material innovations such as liquid metal composites, ionogels, and hydrogels simultaneously optimize electrical performance and mechanical compliance. Emerging design principles such as hierarchical structuring and autonomous repair represent fundamental shifts toward intelligent electrode systems that reduce motion artifacts at the neural-material interface. Critical research gaps are identified, and future directions for developing artifact-free neural recording electrodes are outlined. This review is expected to serve as a roadmap for next-generation neural-material interfaces in wearable bioelectronics.