Jungmin Kim, Ka Ram Kim, Byeongjun Lee, Cheoljeong Park, Seong Jin Cho, Wookhyun Yeo
Wearable electroencephalography (EEG) devices offer a promising solution for continuous brain monitoring outside laboratory settings. However, maintaining stable signal quality over extended periods remains challenging, as skin-mounted EEG systems are prone to contact-induced noise caused by skin deformation and body motion. Here, we present a wrinkle-adaptive kirigami structure and a soft, wearable EEG patch engineered to match subject-specific forehead wrinkle patterns, thereby stabilizing the electrode-skin interface. Our two-step kirigami architecture integrates global conformability with localized strain accommodation, delivering anisotropic deformability and maintaining mechanical stability during facial motion. Leveraging an automated image-based workflow, we enable scalable, individualized generation of kirigami patterns. When integrated into a soft, wireless wearable system, the personalized patch delivers consistently enhanced signal-to-noise ratios across multiple EEG frequency bands, even under diverse motion conditions in at-home sleep settings. This technology demonstrates broad applicability for sleep EEG monitoring and underscores the potential of morphology-aware structural design for next-generation wearable EEG devices.