Underwater Gesture Recognition Meta-Gloves for Marine Immersive Communication
Jiaxu Liu, Lihong Wang, Ruidong Xu, Xinwei Zhang, Jisheng Zhao, Hong Liu, Fuxing Chen, Lijun Qu, Mingwei Tian
Abstract
Rapid advancements in immersive communications and artificial intelligence have created a pressing demand for high-performance tactile sensing gloves capable of delivering high sensitivity and a wide sensing range. Unfortunately, existing tactile sensing gloves fall short in terms of user comfort and are ill-suited for underwater applications. To address these limitations, we propose a flexible hand gesture recognition glove (GRG) that contains high-performance micropillar tactile sensors (MPTSs) inspired by the flexible tube foot of a starfish. The as-prepared flexible sensors offer a wide working range (5 Pa to 450 kPa), superfast response time (23 ms), reliable repeatability (∼10000 cycles), and a low limit of detection. Furthermore, these MPTSs are waterproof, which makes them well-suited for underwater applications. By integrating the high-performance MPTSs with a machine learning algorithm, the proposed GRG system achieves intelligent recognition of 16 hand gestures under water, which significantly extends real-time and effective communication capabilities for divers. The GRG system holds tremendous potential for a wide range of applications in the field of underwater communications.