Deep Multiview Heartwave Authentication
This paper presents a heartwave based authentication method that utilizes an ensemble of deep belief networks (DBNs) under different parameters to increase the reliability of feature extraction. The multiview outputs are further embedded into a single view before inputting into a stacked DBN for cla...
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| Veröffentlicht in: | IEEE transactions on industrial informatics 2019-02, Vol.15 (2), p.777-786 |
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| container_title | IEEE transactions on industrial informatics |
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| creator | Lim, Chin Leng Peter Woo, Wai Lok Dlay, Satnam S. Wu, Di Gao, Bin |
| description | This paper presents a heartwave based authentication method that utilizes an ensemble of deep belief networks (DBNs) under different parameters to increase the reliability of feature extraction. The multiview outputs are further embedded into a single view before inputting into a stacked DBN for classification. The result of the proposed novel architecture achieved a classification rate of 98.3% with 30% training data. Importantly, it is able to perform user classification using heartwave signals acquired under intense physical exercise where heart rate ranges from 50 bpm to as high as 180 bpm. Under extreme physical duress, the heartwave from an individual experiences extreme morphological variations that render conventional classification approaches nonapplicable. |
| doi_str_mv | 10.1109/TII.2018.2874477 |
| format | Article |
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The multiview outputs are further embedded into a single view before inputting into a stacked DBN for classification. The result of the proposed novel architecture achieved a classification rate of 98.3% with 30% training data. Importantly, it is able to perform user classification using heartwave signals acquired under intense physical exercise where heart rate ranges from 50 bpm to as high as 180 bpm. 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Under extreme physical duress, the heartwave from an individual experiences extreme morphological variations that render conventional classification approaches nonapplicable.</description><subject>Authentication</subject><subject>Belief networks</subject><subject>Classification</subject><subject>deep belief network (DBN)</subject><subject>deep learning</subject><subject>discrete wavelet transformation (DWT)</subject><subject>Discrete wavelet transforms</subject><subject>Feature extraction</subject><subject>Heart rate</subject><subject>heartwave</subject><subject>Informatics</subject><subject>multiview spectrum</subject><subject>Network reliability</subject><subject>Physical exercise</subject><subject>Reliability</subject><subject>Senior citizens</subject><subject>Signal classification</subject><subject>Training</subject><issn>1551-3203</issn><issn>1941-0050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1LA0EMhgdRsFbvgpeCB09bk81MJ3ss9aOFipd6HqbTLG6p3To7W_Hfu6XFU17I8ybwKHWLMESE4nExmw1zQB7mbLW29kz1sNCYARg477IxmFEOdKmummYNQBao6KmHJ5Hd4K3dpGpfyc9gKj6mH7-XwbhNn7JNVfCpqrfX6qL0m0ZuTrOvPl6eF5NpNn9_nU3G8ywQUcos-xKN4BL1qgiGwDMyGAwciJc2kBFLbMCPAoxWUnoDmtmzLbjbhBH11f3x7i7W3600ya3rNm67ly5Ha4k06wMFRyrEummilG4Xqy8ffx2CO-hwnQ530OFOOrrK3bFSicg_zppNXjD9AWeFWWk</recordid><startdate>20190201</startdate><enddate>20190201</enddate><creator>Lim, Chin Leng Peter</creator><creator>Woo, Wai Lok</creator><creator>Dlay, Satnam S.</creator><creator>Wu, Di</creator><creator>Gao, Bin</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| source | IEEE Electronic Library (IEL) |
| subjects | Authentication Belief networks Classification deep belief network (DBN) deep learning discrete wavelet transformation (DWT) Discrete wavelet transforms Feature extraction Heart rate heartwave Informatics multiview spectrum Network reliability Physical exercise Reliability Senior citizens Signal classification Training |
| title | Deep Multiview Heartwave Authentication |
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