A Flexible Hydrogel-Based Dual-Modal Sensor System for Intelligent Mechanical Gripping and Wearable Gesture Recognition

Abstract

The triboelectric nanogenerator (TENG) enables efficient mechanical-to-electrical energy conversion, offering green self-powered solutions for flexible electronics and microdevices. However, many TENG-based flexible sensors only support single-signal acquisition, failing to satisfy multimodal sensing requirements. In this work, a flexible sensor with a dual-sensing mechanism is developed, employing PVA/CS hydrogel as the triboelectric layer and PVA/CS/GL hydrogel as the electrode layer. By using TiO2-incorporated silicone rubber as the counter triboelectric layer, the output performance of the device is effectively improved. The optimal incorporation mass ratio and particle size of TiO2 were systematically investigated, and the output voltage reached 248 V. Further introduction of a charge trapping layer enhanced the output signal by 57%. On the basis of the above performance optimization, an encapsulated structured TENG device was fabricated and integrated into a mechanical gripper, enabling the recognition of both the surface material and the mass of objects by combining triboelectric signals and resistance variation of the hydrogel electrode layer. Additionally, the device serves as a motion sensor for hand gesture monitoring. Based on the collected motion signals, machine learning-based classification achieves a recognition accuracy of up to 97.5%. This study provides a promising strategy for flexible sensing, human–machine interaction, and smart wearable applications.