TY  - EJOU
AU  - Kim, Jae Myung 
AU  - Choi, Gyu Ho 
AU  - Kim, Min-Gu 
AU  - Pan, Sung Bum 

TI  - User Recognition System Based on Spectrogram Image Conversion Using EMG Signals
T2  - Computers, Materials \& Continua

PY  - 2022
VL  - 72
IS  - 1
SN  - 1546-2226

AB  - Recently, user recognition methods to authenticate personal identity has attracted significant attention especially with increased availability of various internet of things (IoT) services through fifth-generation technology (5G) based mobile devices. The EMG signals generated inside the body with unique individual characteristics are being studied as a part of next-generation user recognition methods. However, there is a limitation when applying EMG signals to user recognition systems as the same operation needs to be repeated while maintaining a constant strength of muscle over time. Hence, it is necessary to conduct research on multidimensional feature transformation that includes changes in frequency features over time. In this paper, we propose a user recognition system that applies EMG signals to the short-time fourier transform (STFT), and converts the signals into EMG spectrogram images while adjusting the time-frequency resolution to extract multidimensional features. The proposed system is composed of a data pre-processing and normalization process, spectrogram image conversion process, and final classification process. The experimental results revealed that the proposed EMG spectrogram image-based user recognition system has a 95.4% accuracy performance, which is 13% higher than the EMG signal-based system. Such a user recognition accuracy improvement was achieved by using multidimensional features, in the time-frequency domain.
KW  - EMG; user recognition; spectrogram; CNN

DO  - 10.32604/cmc.2022.025213