Efficient fuzzy-controlled and hybrid entropy coding strategy lossless ECG encoder VLSI design for wireless body sensor networks

An efficient VLSI design of a lossless electrocardiogram (ECG) encoder is proposed for wireless body sensor networks. To save wireless transmission power, a novel lossless encoding algorithm had been created for an ECG signal compression. The proposed algorithm consists of a novel adaptive predictor...

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Veröffentlicht in:Electronics letters Jg. 49; H. 17; S. 1
Hauptverfasser: Chen, S-L, Luo, G-A, Lin, T-L
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Stevenage John Wiley & Sons, Inc 15.08.2013
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ISSN:0013-5194, 1350-911X
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Abstract An efficient VLSI design of a lossless electrocardiogram (ECG) encoder is proposed for wireless body sensor networks. To save wireless transmission power, a novel lossless encoding algorithm had been created for an ECG signal compression. The proposed algorithm consists of a novel adaptive predictor based on fuzzy decision control, and a novel hybrid entropy encoder including both a two-stage Huffman and a Golomb-Rice coding. The VLSI architecture contains only 2.71 K gate counts and its core area is 33 929 μm2 synthesized by a 0.18 μm CMOS process. Moreover, this design can be operated at 100 MHz processing rate by consuming only 30 μW. It achieves an average compression rate of 2.56 for the MIT-BIH arrhythmia database. Compared with previous low-complexity and highperformance lossless ECG encoder studies, this design has a higher compression rate, lower power consumption and lower hardware cost than other VLSI designs.
AbstractList An efficient VLSI design of a lossless electrocardiogram (ECG) encoder is proposed for wireless body sensor networks. To save wireless transmission power, a novel lossless encoding algorithm had been created for an ECG signal compression. The proposed algorithm consists of a novel adaptive predictor based on fuzzy decision control, and a novel hybrid entropy encoder including both a two-stage Huffman and a Golomb-Rice coding. The VLSI architecture contains only 2.71 K gate counts and its core area is 33 929 mu m2 synthesized by a 0.18 mu m CMOS process. Moreover, this design can be operated at 100 MHz processing rate by consuming only 30 mu W. It achieves an average compression rate of 2.56 for the MIT-BIH arrhythmia database. Compared with previous low-complexity and highperformance lossless ECG encoder studies, this design has a higher compression rate, lower power consumption and lower hardware cost than other VLSI designs.
An efficient VLSI design of a lossless electrocardiogram (ECG) encoder is proposed for wireless body sensor networks. To save wireless transmission power, a novel lossless encoding algorithm had been created for an ECG signal compression. The proposed algorithm consists of a novel adaptive predictor based on fuzzy decision control, and a novel hybrid entropy encoder including both a two-stage Huffman and a Golomb-Rice coding. The VLSI architecture contains only 2.71 K gate counts and its core area is 33 929 μm2 synthesized by a 0.18 μm CMOS process. Moreover, this design can be operated at 100 MHz processing rate by consuming only 30 μW. It achieves an average compression rate of 2.56 for the MIT-BIH arrhythmia database. Compared with previous low-complexity and highperformance lossless ECG encoder studies, this design has a higher compression rate, lower power consumption and lower hardware cost than other VLSI designs.
Author Chen, S-L
Luo, G-A
Lin, T-L
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Snippet An efficient VLSI design of a lossless electrocardiogram (ECG) encoder is proposed for wireless body sensor networks. To save wireless transmission power, a...
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SubjectTerms Algorithms
Coders
Compressing
Encoders
Entropy
Integrated circuits
Lossless
Very large scale integration
Title Efficient fuzzy-controlled and hybrid entropy coding strategy lossless ECG encoder VLSI design for wireless body sensor networks
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