Abstract：
Sign language recognition is challenging due to the lack of communication between normal and affected people. Many social and physiological impacts are created due to speaking or hearing disability. A lot of different dimensional techniques have been proposed previously to overcome this gap. A sensor-based smart glove for sign language recognition (SLR) proved helpful to generate data based on various hand movements related to specific signs. A detailed comparative review of all types of available techniques and sensors used for sign language recognition was presented in this article. The focus of this paper was to explore emerging trends and strategies for sign language recognition and to point out deficiencies in existing systems. This paper will act as a guide for other researchers to understand all materials and techniques like flex resistive sensor-based, vision sensor-based, or hybrid system-based technologies used for sign language until now.
摘要：
由于正常人和受影响者之间缺乏交流，手语识别具有挑战性。许多社会和生理影响是由于说话或听力障碍造成的。以前已经提出了许多不同的尺寸技术来克服这个差距。用于手语识别（SLR）的基于传感器的智能手套被证明有助于根据与特定标志相关的各种手部动作生成数据。本文对用于手语识别的所有类型的可用技术和传感器进行了详细的比较审查。本文的重点是探索手语识别的新兴趋势和策略，并指出现有系统中的不足。本文将作为其他研究人员的指南，以了解所有材料和技术，如基于柔性电阻传感器，基于视觉传感器，或基于混合系统的技术用于手语到现在为止。
