Real-time hardware architecture of an ECG compression algorithm for IoT health care systems and its VLSI implementation

The Internet of Things (IoT) in the medical and biomedical field proposes new and efficient hardware for healthcare services. Thanks to machine-machine interaction and real-time solutions, the problems of accessibility and reliability are resolved. In addition, increased patient engagement in decisi...

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Vydáno v:	Multimedia tools and applications Ročník 83; číslo 10; s. 30937 - 30961
Hlavní autoři:	Ez-ziymy, Siham, Hatim, Anas, Hammia, Slama
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.03.2024 Springer Nature B.V
Témata:	Algorithms Compression ratio Computer architecture Computer Communication Networks Computer Science Data Structures and Information Theory Electrocardiography Hardware Health services Internet of Things Large scale integration Medical electronics Microprocessors Multimedia Information Systems Real time Special Purpose and Application-Based Systems Track 2: Medical Applications of Multimedia Very large scale integration ECG Compression Smart Systems IT FPGA Hardware Architecture
ISSN:	1573-7721, 1380-7501, 1573-7721
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Abstract	The Internet of Things (IoT) in the medical and biomedical field proposes new and efficient hardware for healthcare services. Thanks to machine-machine interaction and real-time solutions, the problems of accessibility and reliability are resolved. In addition, increased patient engagement in decision-making will drive health service compliance. Vital signals like the electrocardiogram (ECG) are some of the most critical biomedical information to process; it is the subject of several studies. The data flow of those signals is enormous, making real-time transmission a tough job, hence the need to compress these vital signals. Designing efficient hardware compression engines is a promising challenge for efficient real-time transmission. This article introduces a new VLSI (Very-Large-Scale Integration) architecture for an ECG compression engine based on the algorithm presented in the same work. The efficiency of our processor was verified using the MIT BIH databases. We have also implemented it using An FPGA, which reaches a frequency of 170 MHz and 65 n TCMS CMOS. The proposed processor uses 1.85 Kgates and consumes 25 nW with a compression ratio of 3.42.
AbstractList	The Internet of Things (IoT) in the medical and biomedical field proposes new and efficient hardware for healthcare services. Thanks to machine-machine interaction and real-time solutions, the problems of accessibility and reliability are resolved. In addition, increased patient engagement in decision-making will drive health service compliance. Vital signals like the electrocardiogram (ECG) are some of the most critical biomedical information to process; it is the subject of several studies. The data flow of those signals is enormous, making real-time transmission a tough job, hence the need to compress these vital signals. Designing efficient hardware compression engines is a promising challenge for efficient real-time transmission. This article introduces a new VLSI (Very-Large-Scale Integration) architecture for an ECG compression engine based on the algorithm presented in the same work. The efficiency of our processor was verified using the MIT BIH databases. We have also implemented it using An FPGA, which reaches a frequency of 170 MHz and 65 n TCMS CMOS. The proposed processor uses 1.85 Kgates and consumes 25 nW with a compression ratio of 3.42. The Internet of Things (IoT) in the medical and biomedical field proposes new and efficient hardware for healthcare services. Thanks to machine-machine interaction and real-time solutions, the problems of accessibility and reliability are resolved. In addition, increased patient engagement in decision-making will drive health service compliance. Vital signals like the electrocardiogram (ECG) are some of the most critical biomedical information to process; it is the subject of several studies. The data flow of those signals is enormous, making real-time transmission a tough job, hence the need to compress these vital signals. Designing efficient hardware compression engines is a promising challenge for efficient real-time transmission. This article introduces a new VLSI (Very-Large-Scale Integration) architecture for an ECG compression engine based on the algorithm presented in the same work. The efficiency of our processor was verified using the MIT BIH databases. We have also implemented it using An FPGA, which reaches a frequency of 170 MHz and 65 n TCMS CMOS. The proposed processor uses 1.85 Kgates and consumes 25 nW with a compression ratio of 3.42.
Author	Ez-ziymy, Siham Hatim, Anas Hammia, Slama
Author_xml	– sequence: 1 givenname: Siham orcidid: 0000-0003-4140-3896 surname: Ez-ziymy fullname: Ez-ziymy, Siham email: sihamezziymy@gmail.com organization: Laboratory of Energy Engineering, Materials, and Systems, National School of Applied Sciences of Agadir, Ibn Zohr University – sequence: 2 givenname: Anas surname: Hatim fullname: Hatim, Anas organization: Technologies, Information, and Multimedia Team, National School of Applied Sciences of Marrakech, Cadi Ayyad University – sequence: 3 givenname: Slama surname: Hammia fullname: Hammia, Slama organization: Technologies, Information, and Multimedia Team, National School of Applied Sciences of Marrakech, Cadi Ayyad University
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Cites_doi	10.3390/s17102288 10.5405/jmbe.715 10.1109/GCCE.2018.8574652 10.1038/s41598-019-53460-3 10.2139/ssrn.3664586 10.1007/s13755-018-0049-x 10.1016/j.bspc.2019.03.004 10.1109/BioCAS.2012.6418435 10.1587/elex.14.20170524 10.1109/ISNE.2017.7968728 10.1109/CIC.1997.647885 10.1109/ACCESS.2020.2998608 10.1049/el.2015.2202 10.1109/JSEN.2022.3195501 10.1016/j.procs.2016.05.201 10.1007/s00034-019-01198-8 10.1109/ICACCI.2017.8125887 10.1049/el.2012.3505 10.1109/TCSII.2020.2978554 10.1080/03091900701797453 10.1016/j.bspc.2020.101879 10.1088/1742-6596/1964/6/062073 10.1109/TCSI.2018.2867746 10.1109/ICCE-China.2018.8448939 10.4067/S0718-33052012000100002 10.1109/BSN.2016.7516240 10.1109/TVLSI.2016.2638826 10.1016/j.bspc.2015.06.012 10.1109/TBCAS.2016.2591923 10.1016/j.micpro.2019.03.007 10.1109/TBME.2011.2156794 10.1109/TBCAS.2020.2974387 10.1109/LSENS.2022.3157030 10.1109/BioCAS.2012.6418396 10.1587/transient.2017EDL8206 10.1007/s11277-020-07241-1 10.1587/elex.14.20170865 10.1007/s10916-018-0953-2 10.1109/TCSII.2022.3204550
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Snippet	The Internet of Things (IoT) in the medical and biomedical field proposes new and efficient hardware for healthcare services. Thanks to machine-machine...
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SubjectTerms	Algorithms Compression ratio Computer architecture Computer Communication Networks Computer Science Data Structures and Information Theory Electrocardiography Hardware Health services Internet of Things Large scale integration Medical electronics Microprocessors Multimedia Information Systems Real time Special Purpose and Application-Based Systems Track 2: Medical Applications of Multimedia Very large scale integration
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Title	Real-time hardware architecture of an ECG compression algorithm for IoT health care systems and its VLSI implementation
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