Abstract
At the present time, mobile devices such as tablet-type PCs and smart phones have widely penetrated into our daily lives. Therefore, an authentication method that prevents shoulder surfing is needed. We are investigating a new user authentication method for mobile devices that uses surface electromyogram (s-EMG) signals, not screen touching. The s-EMG signals, which are detected over the skin surface, are generated by the electrical activity of muscle fibers during contraction. Muscle movement can be differentiated by analyzing the s-EMG. Taking advantage of the characteristics, we proposed a method that uses a list of gestures as a password in the previous study. In order to realize this method, we have to prepare many gestures that are used to compose passwords. In this paper, we adopted fingerspelling as candidates of such gestures. We measured s-EMG signals of manual kana of The Japanese Sign Language syllabary and examined their ability for the use of passwords of the authentication method.
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Acknowledgements
This work was supported by JSPS KAKENHI Grant Numbers JP17H01736, JP17K00139, JP17K00186, JP18K11268.
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Yamaba, H. et al. (2019). Introduction of Fingerspelling for Realizing a User Authentication Method Using s-EMG. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_67
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DOI: https://doi.org/10.1007/978-3-030-15035-8_67
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