Compressão de Sinais Eletromiográficos Baseada em Técnicas Bidimensionais

Recently, two-dimensional techniques have been successfully employed for encoding surface-electromyography (S- EMG) records, through the use of commercial image encoders as an efficient alternative for that kind of signal. This paper presents an investigation regarding the performance of video and image encoders, when used for compressing S-EMG signals. In addition, a new preprocessing technique is introduced, called euclidean distance sorting (EDS), which has the potential to improve the exploitation of intersegment correlations that com- monly exist in S-EMG records, when they rearranged as images. The experiments were carried out with real isometric records acquired in laboratory, which were first preprocessed and then compressed with the JPEG2000, H.264/AVC, and high efficiency video coding (HEVC) algorithms. One can easily note that the proposed scheme is effective, given that the combination of EDS and the JPEG2000 and HEVC algorithms even outperform state- of-the-art S-EMG compression schemes, in terms of distortion × compression ratio.