Hand gestures are a significant and global form of non-verbal communication that raises the boundaries of language and culture. From simple wave to complex sign language recognition (SLR), these gestures articulate emotions, intentions, and meanings, weaving a rich tapestry of human interaction. In a world increasingly shaped by digital innovation, the study of hand gesture recognition (HGR) has surged to the forefront, unlocking possibilities across human–computer interaction (HCI), virtual reality, health care, and robotics. For the hearing-impaired community, hand gestures, especially sign language, stand as the cornerstone of communication. Yet, a significant barrier emerges when interacting with those who are unfamiliar with this visual language. This requires an urgent need for technological interventions, not merely as tools but as bridges that foster understanding and inclusivity. Accessibility has become more than a technical ambition; it is a mission to enhance the quality of life for millions who rely on gestures to connect with the world. This paper delves into updates made in sign language research within vision-based hand gesture recognition systems. By precisely extracting articles from reputed online databases, we aimed to map the progress in this domain whilst identifying critical gaps that warrant further attention. Each year, a wealth of studies is published in journals and conference proceedings, reflecting the tireless efforts of researchers worldwide. Most of this research converges on three pivotal aspects: how data are acquired, the environments in which these systems operate, and the representation of hand gestures themselves. Each of these dimensions presents unique challenges and opportunities, shaping the trajectory of future innovations.