VLSI implementation of low‐power cost‐efficient lossless ECG encoder design for wireless healthcare monitoring application
An efficient VLSI architecture of a lossless ECG encoding circuit is proposed for wireless healthcare monitoring applications. To reduce the transmission and storage data, a novel lossless compression algorithm is proposed for ECG signal compression. It consists of a novel adaptive rending predictor...
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| Vydané v: | Electronics letters Ročník 49; číslo 2; s. 91 - 93 |
|---|---|
| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
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Stevenage
The Institution of Engineering and Technology
01.01.2013
Institution of Engineering and Technology |
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| ISSN: | 1350-911X, 0013-5194, 1350-911X |
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| Abstract | An efficient VLSI architecture of a lossless ECG encoding circuit is proposed for wireless healthcare monitoring applications. To reduce the transmission and storage data, a novel lossless compression algorithm is proposed for ECG signal compression. It consists of a novel adaptive rending predictor and a novel two‐stage entropy encoder based on two Huffman coding tables. The proposed lossless ECG encoder design was implemented using only simple arithmetic units. To improve the performance, the proposed ECG encoder was designed by pipeline technology and implemented the two‐stage entropy encoder by the architecture of a look‐up table. The VLSI architecture of this work contains 3.55 K gate counts and its core area is 45987 µm2 synthesised by a 0.18 µm CMOS process. It can operate at 100 MHz processing rate with only 36.4 µW. The data compression rate reaches an average value 2.43 for the MIT‐BIH Arrhythmia Database. Compared with the previous low‐complexity and high performance techniques, this work achieves lower hardware cost, lower power consumption, and a better compression rate than other lossless ECG encoder designs. |
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| AbstractList | An efficient VLSI architecture of a lossless ECG encoding circuit is proposed for wireless healthcare monitoring applications. To reduce the transmission and storage data, a novel lossless compression algorithm is proposed for ECG signal compression. It consists of a novel adaptive rending predictor and a novel two‐stage entropy encoder based on two Huffman coding tables. The proposed lossless ECG encoder design was implemented using only simple arithmetic units. To improve the performance, the proposed ECG encoder was designed by pipeline technology and implemented the two‐stage entropy encoder by the architecture of a look‐up table. The VLSI architecture of this work contains 3.55 K gate counts and its core area is 45987 µm 2 synthesised by a 0.18 µm CMOS process. It can operate at 100 MHz processing rate with only 36.4 µW. The data compression rate reaches an average value 2.43 for the MIT‐BIH Arrhythmia Database. Compared with the previous low‐complexity and high performance techniques, this work achieves lower hardware cost, lower power consumption, and a better compression rate than other lossless ECG encoder designs. An efficient VLSI architecture of a lossless ECG encoding circuit is proposed for wireless healthcare monitoring applications. To reduce the transmission and storage data, a novel lossless compression algorithm is proposed for ECG signal compression. It consists of a novel adaptive rending predictor and a novel two‐stage entropy encoder based on two Huffman coding tables. The proposed lossless ECG encoder design was implemented using only simple arithmetic units. To improve the performance, the proposed ECG encoder was designed by pipeline technology and implemented the two‐stage entropy encoder by the architecture of a look‐up table. The VLSI architecture of this work contains 3.55 K gate counts and its core area is 45987 µm2 synthesised by a 0.18 µm CMOS process. It can operate at 100 MHz processing rate with only 36.4 µW. The data compression rate reaches an average value 2.43 for the MIT‐BIH Arrhythmia Database. Compared with the previous low‐complexity and high performance techniques, this work achieves lower hardware cost, lower power consumption, and a better compression rate than other lossless ECG encoder designs. |
| Author | Wang, J.‐G Chen, S.‐L. |
| Author_xml | – sequence: 1 givenname: S.‐L. surname: Chen fullname: Chen, S.‐L. email: chrischen@cycu.edu.tw organization: Chung Yuan Christian University – sequence: 2 givenname: J.‐G surname: Wang fullname: Wang, J.‐G organization: Beijing Institute of Technology |
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| Cites_doi | 10.1109/JSYST.2009.2032440 10.1049/el:20081319 10.1049/el.2010.3191 10.1109/TCE.2011.5735512 10.1109/TBME.2006.888820 |
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| Keywords | Signal compression High performance Lossless circuit VLSI circuit Circuit design Pipeline processor Huffman code Data compression Lossless compression Information rate Low power Adaptive method Energy savings Pipeline Storage Electrocardiography Wireless network Arrhythmia (physiology) Monitoring |
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| References_xml | – volume: 44 start-page: 1182 issue: 20 year: 2008 end-page: 1183 article-title: Effective quality‐controlled SPIHT‐based ECG coding strategy under noise environments publication-title: Electron. Lett. – volume: 54 start-page: 410 issue: 3 year: 2007 end-page: 418 article-title: ECG signal compression based on Burrows‐Wheeler transformation and inversion ranks of linear prediction publication-title: IEEE Trans. Biomed. Eng. – volume: 57 start-page: 267 issue: 1 year: 2011 end-page: 273 article-title: Mixed bio‐signal lossless data compressor for portable brain‐heart monitoring systems publication-title: IEEE Trans. Consum. Electron. – volume: 3 start-page: 398 issue: 4 year: 2009 end-page: 409 article-title: Wireless body sensor network with adaptive low power design for biometrics and healthcare applications publication-title: IEEE Syst. J. – volume: 47 start-page: 87 issue: 2 year: 2011 end-page: 89 article-title: Improved ECG compression method using discrete consine transform publication-title: Electron. Lett. – ident: e_1_2_7_2_1 doi: 10.1109/JSYST.2009.2032440 – ident: e_1_2_7_3_1 doi: 10.1049/el:20081319 – ident: e_1_2_7_4_1 doi: 10.1049/el.2010.3191 – ident: e_1_2_7_6_1 doi: 10.1109/TCE.2011.5735512 – ident: e_1_2_7_5_1 doi: 10.1109/TBME.2006.888820 |
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| SubjectTerms | adaptive rending predictor Applied sciences arithmetic unit Biological and medical sciences CMOS integrated circuits CMOS process Coding, codes computerised monitoring data compression ECG signal compression electrocardiography Electrocardiography. Vectocardiography Electrodiagnosis. Electric activity recording Electronics entropy codes entropy encoder Exact sciences and technology frequency frequency 100 MHz gate counts health care Huffman codes Huffman coding table Information, signal and communications theory Integrated circuits Integrated circuits by function (including memories and processors) Investigative techniques, diagnostic techniques (general aspects) lookup table lossless compression algorithm lossless ECG encoder design Medical sciences medical signal processing MIT‐BIH Arrhythmia database Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques patient monitoring pipeline arithmetic pipeline technology power power 36.4 muW Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices Signal and communications theory size size 0.18 mum table lookup Telecommunications and information theory VLSI VLSI architecture wireless healthcare monitoring application |
| Title | VLSI implementation of low‐power cost‐efficient lossless ECG encoder design for wireless healthcare monitoring application |
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