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表面筋電位を用いた個人認証のための指文字ベースジェスチャの評価
http://hdl.handle.net/10458/00010207
http://hdl.handle.net/10458/0001020775511b58-cb22-4f20-8182-dddfcda3cd40
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
本文 (1.9 MB)
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| Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
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| 公開日 | 2021-06-08 | |||||
| タイトル | ||||||
| タイトル | 表面筋電位を用いた個人認証のための指文字ベースジェスチャの評価 | |||||
| 言語 | ja | |||||
| タイトル | ||||||
| タイトル | Evaluation of a Set of Manual Alphabets Based Gestures for a User Authentication Method Using s-EMG | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | jpn | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | User Authentication | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | s-EMG | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Manual Alphabets | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Support Vector Machine | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | departmental bulletin paper | |||||
| 著者 |
山場, 久昭
× 山場, 久昭× 長友, 勇樹× 油田, 健太郎× 岡崎, 直宣× Nagatomo, Yuki |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | At the present time, mobile devices such as tablet-type PCs and smart phones have widely penetrated into our daily lives. This movement caused a new threat that a stranger takes a peek at our authentication operations on our touch screens and steals our passwords and steals our important information and data in our mobile devices. This forced us to develop new authentication method that can prevent this sort of crime called a shoulder surfing attack. We have investigated 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, can be used to identify who generated the signals and which gesture he made. We introduced a pass-gesture, which is a list of hand signals, to realize the s-EMG based authentication method. In order to realize this method, we have to prepare a sufficient number of gestures that are used to compose passwords. In this paper, we adopted figerspelling as candidates of such gestures. We measured s-EMG signals of manual kana of the Japanese Sign Language syllabary and evaluated their potential as the important element of the user authentication method. First, we attempted to choose ten gestures from the manual alphabets. Concretely, we made some gesutre groups according to their shapes and selected one gesture from each group. Next, we evaluated a series of experiments to identify the gestures from each other. Support Vector Machines were used in the exepriments. The results shows that the gesture set has can be identified to some extent. | |||||
| 言語 | en | |||||
| 書誌情報 |
ja : 宮崎大学工学部紀要 en : Memoirs of Faculty of Engineering, University of Miyazaki 巻 49, p. 233-237, 発行日 2020-09-30 |
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| 出版者 | ||||||
| 出版者 | 宮崎大学工学部 | |||||
| 言語 | ja | |||||
| 出版者 | ||||||
| 出版者 | Faculty of Engineering, University of Miyazaki | |||||
| 言語 | en | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 05404924 | |||||
| 書誌レコードID | ||||||
| 収録物識別子タイプ | NCID | |||||
| 収録物識別子 | AA00732558 | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
