A Study of Personal Recognition Method Based on EMG Signal
文献类型：期刊论文
| 作者 | Lu, Lijing3 ; Mao, Jingna2; Wang, Wuqi2; Ding, Guangxin2; Zhang, Zhiwei1,2
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| 刊名 | IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS
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| 出版日期 | 2020-08-01 |
| 卷号 | 14期号:4页码:681-691 |
| 关键词 | Electromyography personal identification personal verification discrete wavelet transform ExtraTreesClassifer continuous wavelet transform convolutional neural networks transfer learning siamese network |
| ISSN号 | 1932-4545 |
| DOI | 10.1109/TBCAS.2020.3005148 |
| 通讯作者 | Mao, Jingna(jingna.mao@ia.ac.cn) |
| 英文摘要 | With the increasing development of internet, the security of personal information becomes more and more important. Thus, variety of personal recognition methods have been introduced to ensure persons' information security. Traditional recognition methods such as Personal Identification Number (PIN), or Identification tag (ID) are vulnerable to hackers. Then the biometric technology, which uses the unique physiological characteristics of human body to identify user information has been proposed. But the biometrics widely used at present such as human face, fingerprint, iris, and voice can also be forged and falsified. The biometric with living body features such as electromyography (EMG) signal is a good method to achieve aliveness detection and prevent the spoofing attacks. However, there are few studies on personal recognition based on EMG signal. According to the application context, personal recognition system may operate either in identification mode or verification mode. In the personal identification mode, the system recognizes an individual by searching the templates of all the users in the database for a match. While in the personal verification mode, the system validates a person's identity by comparing the captured features with her or his own template(s) stored in the system database. In this paper, both EMG-based personal identification method and EMG-based personal verification method are investigated. First, the Myo armband is placed on the right forearm (specifically, the height of the radiohumeral joint) of 21 subjects to collect the surface EMG signal under hand-open gesture. Then, two different methods are proposed for EMG-based personal identification, i.e., personal identification method based on Discrete Wavelet Transform (DWT) and ExtraTreesClassifier, and personal identification method based on Continuous Wavelet Transform (CWT) and Convolutional Neural Networks (CNN). Experiments with 21 subjects show that the identification accuracy of this two methods can achieve 99.206% and 99.203% respectively. Then based on the identification method using CWT and CNN, transfer learning algorithm is adopted to solve the model update problem when new data is added. Finally, an EMG-based personal verification method using CWT and siamese networks is proposed. Experiments show that the verification accuracy of this method can achieve 99.285%. |
| WOS关键词 | MOTOR UNIT ; CLASSIFICATION |
| 资助项目 | Strategic Priority Research Program of Chinese Academy of Sciences[XDB32040200] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000562099400006 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | Strategic Priority Research Program of Chinese Academy of Sciences |
| 源URL | [http://ir.ia.ac.cn/handle/173211/40508]  |
| 专题 | 国家专用集成电路设计工程技术研究中心_信号处理及脑机接口芯片 |
| 通讯作者 | Mao, Jingna |
| 作者单位 | 1.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lu, Lijing,Mao, Jingna,Wang, Wuqi,et al. A Study of Personal Recognition Method Based on EMG Signal[J]. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS,2020,14(4):681-691. |
| APA | Lu, Lijing,Mao, Jingna,Wang, Wuqi,Ding, Guangxin,&Zhang, Zhiwei.(2020).A Study of Personal Recognition Method Based on EMG Signal.IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS,14(4),681-691. |
| MLA | Lu, Lijing,et al."A Study of Personal Recognition Method Based on EMG Signal".IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 14.4(2020):681-691. |
入库方式： OAI收割
来源：自动化研究所
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