Gesture recognition, as a core technology of human–computer interaction, has broad application prospects and brings new technical possibilities for smart homes, medical care, sports training, and other fields. Compared with the traditional human–computer interaction models based on PC use with keyboards and mice, gesture recognition-based human–computer interaction modes can transmit information more naturally, flexibly, and intuitively, which has become a research hotspot in the field of human–computer interaction in recent years. This paper described the current status of gesture recognition technology, summarized the principles and development history of electromagnetic wave sensor recognition, stress sensor recognition, electromyographic sensor recognition, and visual sensor recognition, and summarized the improvement of this technology by researchers in recent years through the direction of sensor structure, selection of characteristic signals, the algorithm of signal processing, etc. By sorting out and comparing the typical cases of the four implementations, the advantages and disadvantages of each implementation and the application scenarios were discussed from the two aspects of dataset size and accuracy. Based on the abovementioned discussion, the problems and challenges of current gesture recognition technology were discussed in terms of the biocompatibility of sensor structures, wearability and adaptability, stability, robustness, and crossover of signal acquisition and analysis algorithms, and the future development directions in this field were proposed.

Stimulated Brillouin scattering (SBS) suppression and phase demodulation are two fundamental issues in remote interferometric fiber sensing systems. A method is proposed for achieving simultaneous SBS suppression and phase-generated carrier (PGC) demodulation in remote interferometric fiber sensing systems, with only the use of an electro-optic phase modulator (PM). A single-frequency laser is phase-modulated by a PM to generate multi-sideband light, which can suppress SBS in long-haul fibers and generate PGC combined with the optical fiber interferometer. Then, the phase signal of the optical fiber interferometer can be demodulated by the PGC demodulation method. A detailed theoretical analysis and the experimental results are presented to confirm the feasibility of the method. The results show that the proposed method can achieve high-performance PGC demodulation with much higher bandwidth and larger dynamic range than the conventional method. Meanwhile, the SBS and its induced phase noise can be suppressed effectively. This work presents a simple setup for SBS suppression and PGC demodulation in a remote interferometric fiber sensing system. The proposed method shows great potential for application in remote and large-scale interferometric fiber sensing systems.

With increasing demand for ocean exploration, underwater tasks become more complex. Soft robotic hands leverage flexible structures and biomimetic properties to provide a strong alternative to rigid robotic hands. However, most existing studies on underwater soft robotic hands focus on novel materials and improved biomimetic structural designs. These systems often suffer from low sensing accuracy and poor human–machine interaction performance, making it difficult to achieve real-time and precise control in complex environments. Here, we propose a Light-Perception-Based Underwater Digital Twin Hand Interactive Control System (LP-UDTHS) that integrates a multi-degree-of-freedom (multi-DOF) biomimetic pneumatic soft robotic hand with a wearable data glove based on fiber Bragg grating (FBG) sensors. By fusing data from FBGs, RGB cameras, and inertial measurement units (IMUs), and optimizing control strategies through reinforcement learning, we established a light-dominated perception–control–feedback closed-loop system that significantly enhances the control performance of the system in complex and dynamic underwater environments. With light as the information carrier, the system integrates a data glove with high strain sensitivity (1.148 pm/µε, linearity = 0.9996) and high bending sensitivity (26.667 pm/°, linearity = 0.9791). It achieves four-dimensional collaborative interaction and control between the human operator, the machine, the virtual space, and the environment. The system achieves posture monitoring and precise grasping control across various underwater scenarios. It demonstrates advantages such as low cost, high precision, rapid response, strong interference resistance, and stable interaction. This establishes a new paradigm for underwater intelligent equipment by integrating light sensing with digital twin technology, offering broad prospects for future underwater operations.