An intelligent triboelectric sensing system for monitoring and early warning of dry eye syndrome

For recent years, the heavy and prolonged use of electronic devices has resulted in a growing population of dry eye syndrome especially for younger individuals. Due to a lack of public awareness, the rate of seeking medical consultations remains relatively low. The advancement in smart wearable technology has opened up numerous possibilities for early observation of the symptoms such as frequent eye blinking and implementation of subsequent healthcare. In this study, we present a personalized monitoring-feedback system based on a selfpowered, wearable, stretchable triboelectric sensor and matching counting module, image display module, and human-computer interaction module. The system is capable of detecting subtle biomechanical signals in the human body with exceptional sensitivity, such as eye blinking. The electronically processed electrical signals can activate a coupled counter and transmit information to mobile devices through the Internet of Things (IoT). This enables automatic processing and interaction with users, providing reminders and correction information regarding eye-related behavior. Through animal and volunteer experiments, we validate the accurate identification of eye-related behavior and the provision of appropriate feedback. This work proposes a promising technological approach for monitoring, early warning and management of dry eye syndrome.