Speech and hearing-impaired individuals encounter significant challenges in effective interaction within a predominantly spoken language-oriented society. Several individuals with difficulties with hearing or communicating non-verbally use sign language as a vital means of communication. There are communication gaps between members of these groups and non-native speakers of sign language or who are unable to understand signs in daily interactions. Techniques such as gesture image processing, gesture recognition, and conversion of speech-to-text and text-to-speech have led to the development of innovative methods for the growth of communication. The review aims to analyze various gesture recognition technologies to classify sign language signals and to communicate effectively. Besides, the classification of sign language gestures using wearable sensor technology was discussed. About 1350 articles from 2011 to 2023 were found using the keywords in the search. A total of 250 articles were included based on the title. Following the review of the abstracts, 238 articles were removed. Twelve papers underwent full-text examination to identify various trends, ideal implications, and the communication gaps that exist among them. In particular, a variety of study results on sign language gesture recognition systems were gathered and analyzed. The results of the literature review contribute to the advancement of robust, human-centered wearable systems-based sensory gloves for the benefit of individuals with hearing and speech impairments.