A Real Time Sign Language Interpretation of forearm based on Data Acquisition Method

The popularity of the field of electromyography has reached at a height in the past few years. There are several factors that contribute to the achievement of such a height like sensor technology advancement, exponential rise of computational abilities of computer, progress in understanding of human body and increasing awareness of benefits of interdisciplinary studies. The posture and orientation are the key for the identification of the EMG signal. Sign language is based on the use of specific sign or gesture. Individual sign has three components i.e. shape of hand, movement and location of hand. Multiple signs can be identified with different postures and orientation. This paper presents the fundamental concepts of analog to digital data acquisition with the goals of recording better quality of EMG signals generated by the posture and orientation of muscles of hands. In this paper, a wireless and wearable multi sensor EMG system is developed to translate sign language into spoken language for the dumb, so that they can convey their message through sign to the person who don't know sign language by converting it into spoken form. The paper gives the introduction of EMG, calculation of mean absolute value by short time analysis, knowledge of sensors method and experimental setup along with the scope of EMG and result of the experiment and the recordings obtained.