Capacitive sensing for facial expression recognition and beyond: Materials, architectures, and wearable applications

Capacitive sensing is rapidly emerging as a transformative technology for wearable electronics, offering compelling combination of flexibility, sensitivity, and unobtrusiveness. This review explores the latest developments in capacitive sensors tailored for health monitoring and facial expression recognition (FER). We examine pressure, proximity, and strain sensors, with a focus on their ability to detect subtle facial muscle movements linked to emotional and cognitive states. Emphasis is placed on wearable form factors, such as smart glasses, and their ability to support FER through Action Unit (AU) analysis, as defined by the Facial Action Coding System (FACS). We critically compare capacitive-based approaches to traditional FER techniques, including camera-based systems, electromyography (EMG), electrooculography (EOG), and magnetic sensing, highlighting key advantages in terms of user comfort, privacy compliance, and robustness environmental noise. Advances in materials, such as metals and their other forms, graphene, carbon nanotubes (CNTs), silicone elastomers, and hydrogels, and fabrication techniques, like additive manufacturing, inkjet printing, 3D printing, laser and micro-patterning, are surveyed for their role in improving device performance and integration. Finally, we outline current limitations, including motion and signal artifacts and their variability with environmental interference, and discuss future research opportunities such as multimodal fusion, calibration, machine learning, and energy-efficient design. Together, these insights, position capacitive sensors as a foundational technology for the next generation of affective and physiological wearables.