عرض بسيط للتسجيلة

المؤلفIbtehaz N.
المؤلفChowdhury M.E.H.
المؤلفKhandakar A.
المؤلفKiranyaz, Mustafa Serkan
المؤلفRahman M.S.
المؤلفTahir A.
المؤلفQiblawey Y.
المؤلفRahman T.
تاريخ الإتاحة2022-04-26T12:31:19Z
تاريخ النشر2021
اسم المنشورIEEE Transactions on Emerging Topics in Computational Intelligence
المصدرScopus
المعرّفhttp://dx.doi.org/10.1109/TETCI.2021.3131374
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85110936234&doi=10.1109%2fTETCI.2021.3131374&partnerID=40&md5=3bb87b7723ecebaae10a861b53cce7fb
معرّف المصادر الموحدhttp://hdl.handle.net/10576/30597
الملخصIn recent years, physiological signal-based authentication has shown great promises, for its inherent robustness against forgery. Electrocardiogram (ECG) signal, being the most widely studied biosignal, has also received the highest level of attention in this regard. It has been proven with numerous studies that by analyzing ECG signals from different persons, it is possible to identify them, with acceptable accuracy. In this work, we present, EDITH, a deep learning-based framework for ECG biometrics authentication system. Moreover, we hypothesize and demonstrate that Siamese architectures can be used over typical distance metrics for improved performance. We have evaluated EDITH using 4 commonly used datasets and outperformed the prior works using a fewer number of beats. EDITH performs competitively using just a single heartbeat (96<formula><tex>$\sim$</tex></formula>99.75&#x0025; accuracy) and can be further enhanced by fusing multiple beats (100&#x0025; accuracy from 3 to 6 beats). Furthermore, the proposed Siamese architecture manages to reduce the identity verification Equal Error Rate (EER) to 1.29 &#x0025;. A limited case study of EDITH with real-world experimental data also suggests its potential as a practical authentication system
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعAuthentication
Biological systems
Deep learning
Electrocardiography
Network architecture
1d convolutional network
1d siamese network
Biological system modeling
Biometric (access control)
Convolutional networks
Deep learning
Electrocardiogram signal
Electrocardiogram-ID
Heart beats
Task analysis
Biometrics
العنوانEDITH : ECG Biometrics Aided by Deep Learning for Reliable Individual Authentication
النوعArticle
dc.accessType Abstract Only


الملفات في هذه التسجيلة

الملفاتالحجمالصيغةالعرض

لا توجد ملفات لها صلة بهذه التسجيلة.

هذه التسجيلة تظهر في المجموعات التالية

عرض بسيط للتسجيلة