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dc.contributor.authorAit Si Ali, Amine
dc.contributor.authorZhai, Xiaojun
dc.contributor.authorAmira, Abbes
dc.contributor.authorBensaali, Faycal
dc.contributor.authorRamzan, Naeem
dc.date.accessioned2016-11-10T16:47:10Z
dc.date.available2016-11-10T16:47:10Z
dc.date.issued2016-05-01
dc.identifier.citationAli, A. et al, (2016) 'Heterogeneous implementation of ECG encryption and identification on the Zynq SoC', Proceedings of the IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 1-3 May, Washington DC, USAen
dc.identifier.isbn9781509023561
dc.identifier.doi10.1109/FCCM.2016.44
dc.identifier.urihttp://hdl.handle.net/10545/620807
dc.description.abstractThis paper presents an innovative and safe connected health solution for human identification. The system consists of the encryption and decryption of ECG signals using the advanced encryption standard (AES) as well as the recognition of individuals based on ECG biometrics. Heterogeneous and efficient implementation of the proposed system has been performed on a Xilinx ZC702 Zynq based prototyping board. Various IP-cores have been created based on the high level synthesis (HLS) implementation of the AES cipher, AES decipher and ECG identification blocks. The proposed hardware implementation has shown promising results since it met the real-time requirements and outclassed current field programmable gate array (FPGA) based systems in multiple key metrics including power consumption, processing time and hardware resources usage. The implemented system needs 10.71 ms to process one ECG sample and consumes 107mW while using only 30% of all available on-chip resources.
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/document/7544767/en
dc.relation.urlhttp://fccm.org/2016/en
dc.subjectElectrocardiographyen
dc.subjectHardwareen
dc.subjectEncryptionen
dc.subjectCiphersen
dc.subjectCiphersen
dc.subjectSoftwareen
dc.titleHeterogeneous implementation of ECG encryption and identification on the Zynq SoCen
dc.typeMeetings and Proceedingsen
dc.contributor.departmentUniversity of Derbyen
dc.identifier.journalProceedings of the IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)en
html.description.abstractThis paper presents an innovative and safe connected health solution for human identification. The system consists of the encryption and decryption of ECG signals using the advanced encryption standard (AES) as well as the recognition of individuals based on ECG biometrics. Heterogeneous and efficient implementation of the proposed system has been performed on a Xilinx ZC702 Zynq based prototyping board. Various IP-cores have been created based on the high level synthesis (HLS) implementation of the AES cipher, AES decipher and ECG identification blocks. The proposed hardware implementation has shown promising results since it met the real-time requirements and outclassed current field programmable gate array (FPGA) based systems in multiple key metrics including power consumption, processing time and hardware resources usage. The implemented system needs 10.71 ms to process one ECG sample and consumes 107mW while using only 30% of all available on-chip resources.


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