The purpose of this study was to propose a low-cost and real-time recognition system using a  sensory glove, which has 17 sensors with 65 channels to capture static sign data of the Malaysian  sign language (MSL). The study uses an experimental design. Five participants  well-known  MSL   were  chosen  to  perform  75  gestures  throughout  wear sensory glove. This research was carried  out in six phases as follows: Phase I involved a review of literature via a systematic review  approach to identify the relevant set of articles that helped formulate the research questions.  Phase II focused on the analysis of hand anatomy, hand kinematic, and hand gestures to help  understand the nature of MSL and to define the glove requirements. In Phase III, DataGlove was  designed and developed based on the glove requirements to help optimize the best functions of the  glove. Phase IV involved the pre-processing, feature extraction, and classification of the data  col.....

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