Underwater Gesture Recognition Meta-Gloves for Marine Immersive Communication

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 highperformance 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.

Strain-Temperature Dual Sensor Based on Deep Learning Strategy for Human–Computer Interaction Systems

“…Traditional conductive materials such as metals and organic semiconductors have limitations in flexible electronics due to issues such as a lack of elasticity and biocompatibility and low Seebeck coefficients. , As a result, hydrogels are emerging as a promising material platform for flexible electronics, offering excellent properties, including flexibility, stretchability, and the ability to detect environmental stimuli such as pressure, strain, and temperature simultaneously, and the advantages of action monitoring under complex conditions through deep learning and super hydrophobicity. − For example, inspired by the flexible tube feet of starfish, Liu et al proposed a flexible gesture recognition glove (GRG), and the fabricated flexible sensor provided a wide working range, reliable repeatability, and low detection limits. By combining high-performance MPTS with machine learning algorithms, the proposed GRG system achieved intelligent recognition of 16 underwater gestures …”