Sign language handshape recognition using Myo Armband
Amina Ben Haj Amor, Oussama El Ghoul, Mohamed Jemni · 2019
In this work, we propose a new approach for recognizing sign language hand shapes using electromyogram (EMG) signals. The processed signal is obtained from the Myo armband witch uses eight sensors. The new approach is based on MFCC and DTW methods and the K-NN classifier. We also present the experiments carried out for the validation of the proposed approach as well as the obtained results.