@article{oai:miyazaki-u.repo.nii.ac.jp:00005239,
 author = {黒木, 聡舜 and Kurogi, Tokiyoshi and Yamaba, Hisaaki and 山場, 久昭 and 久保田, 真一郎 and Kubota, Shin-Ichiro and Katayama, Tetsuro and 片山, 徹郎 and Okazaki, Naonobu and 岡崎, 直宣 and 黒木, 聡舜 and Kurogi, Tokiyoshi and 久保田, 真一郎 and Kubota, Shin-Ichiro},
 journal = {宮崎大学工学部紀要, Memoirs of Faculty of Engineering, University of Miyazaki},
 month = {Jul},
 note = {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 generated by the electrical activity of muscle fibers during contraction, are detected over the skin surface. Muscle movement can be differentiated by analyzing the s-EMG. We proposed a method that uses a list of gestures as a password in the previous study. In this paper, results of experiments are presented that was carried out to investigate the performance of the method identifying gestures from s-EMG signals using support vector machines (SVM). An experiment to identify users from s-EMG signals was carried out at the same time. The performance of SVM as a classifier of our method was also discussed according to the results.},
 pages = {251--256},
 title = {筋電位による個人認証システム実現のための筋電波形の特徴量に関する検討},
 volume = {46},
 year = {2017},
 yomi = {クロギ, トキヨシ and ヤマバ, ヒサアキ and クボタ, シンイチロウ and カタヤマ, テツロウ and オカザキ, ナオノブ and クロギ, トキヨシ and クボタ, シンイチロウ}
}