ECG Lossless/Lossy Compression Algorithms Utilizing the QRS-wave Difference and Its Realization on the Wireless Holter System

碩士 === 國立成功大學 === 電機工程學系碩博士班 === 101 === With the aging population in the world and people’ awareness of health improved, “Remote Home Care System” is gradually taken seriously. To avoid the burden of bandwidth and memory capacity, which are sprung from the ECG holter system, we present the lossless...

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Main Authors: Pei-ChenTai, 戴佩真
Other Authors: Sheau-Fang Lei
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/63307832990186486148
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spelling ndltd-TW-101NCKU54422572015-10-13T22:51:45Z http://ndltd.ncl.edu.tw/handle/63307832990186486148 ECG Lossless/Lossy Compression Algorithms Utilizing the QRS-wave Difference and Its Realization on the Wireless Holter System 利用差分QRS波之無失真/失真性心電訊號壓縮演算法與無線心電圖量測系統實現 Pei-ChenTai 戴佩真 碩士 國立成功大學 電機工程學系碩博士班 101 With the aging population in the world and people’ awareness of health improved, “Remote Home Care System” is gradually taken seriously. To avoid the burden of bandwidth and memory capacity, which are sprung from the ECG holter system, we present the lossless and lossly compression algorithms with the method of QRS-wave difference and apply to the Wireless Holter System. With different application requirements, users can choose high-compression rate or perfect reconstructed algorithms to obtain higher signal quality and to reduce more storage memory size. For the proposed lossless compression algorithm, we use backward difference and QRS-wave difference to process ECG signal, and huffman encoding to produce the compressed data. In the lossy compression algorithm respect, we take fast fourier transform (FFT) as the kernel function which belongs to the lossy compression. After the procedure of QRS-wave difference, we partition off the RR interval and interpolate to 256 points. And then, we can get the compressed data by using FFT coefficients to the procedure of backward difference, run length encoding and Huffman coding. The proposed algorithms were evaluated by using all patterns from MIT-BIH arrhythmia database and the test pattern which we measure the ECG signal from our ECG read-out circuit. For the proposed lossless algorithm, the average CR is 2.66 and 1.22. Furthermore, for the proposed lossy algorithm, the analytic results such as CR, PRD, PRDB, PRDN, RMS, SNR, and QS’s value is 6.69, 0.13, 1.37, 1.90, 1.20, 35.07 and 53.69. By using the test pattern which we measure the ECG signal, the analytic results such as CR, PRD, PRDB, PRDN, RMS, SNR, and QS’s value is 5.44, 0.14, 0.99, 3.46, 37.28, 30.01 and 40.21. Sheau-Fang Lei 雷曉方 2013 學位論文 ; thesis 86 zh-TW
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description 碩士 === 國立成功大學 === 電機工程學系碩博士班 === 101 === With the aging population in the world and people’ awareness of health improved, “Remote Home Care System” is gradually taken seriously. To avoid the burden of bandwidth and memory capacity, which are sprung from the ECG holter system, we present the lossless and lossly compression algorithms with the method of QRS-wave difference and apply to the Wireless Holter System. With different application requirements, users can choose high-compression rate or perfect reconstructed algorithms to obtain higher signal quality and to reduce more storage memory size. For the proposed lossless compression algorithm, we use backward difference and QRS-wave difference to process ECG signal, and huffman encoding to produce the compressed data. In the lossy compression algorithm respect, we take fast fourier transform (FFT) as the kernel function which belongs to the lossy compression. After the procedure of QRS-wave difference, we partition off the RR interval and interpolate to 256 points. And then, we can get the compressed data by using FFT coefficients to the procedure of backward difference, run length encoding and Huffman coding. The proposed algorithms were evaluated by using all patterns from MIT-BIH arrhythmia database and the test pattern which we measure the ECG signal from our ECG read-out circuit. For the proposed lossless algorithm, the average CR is 2.66 and 1.22. Furthermore, for the proposed lossy algorithm, the analytic results such as CR, PRD, PRDB, PRDN, RMS, SNR, and QS’s value is 6.69, 0.13, 1.37, 1.90, 1.20, 35.07 and 53.69. By using the test pattern which we measure the ECG signal, the analytic results such as CR, PRD, PRDB, PRDN, RMS, SNR, and QS’s value is 5.44, 0.14, 0.99, 3.46, 37.28, 30.01 and 40.21.
author2 Sheau-Fang Lei
author_facet Sheau-Fang Lei
Pei-ChenTai
戴佩真
author Pei-ChenTai
戴佩真
spellingShingle Pei-ChenTai
戴佩真
ECG Lossless/Lossy Compression Algorithms Utilizing the QRS-wave Difference and Its Realization on the Wireless Holter System
author_sort Pei-ChenTai
title ECG Lossless/Lossy Compression Algorithms Utilizing the QRS-wave Difference and Its Realization on the Wireless Holter System
title_short ECG Lossless/Lossy Compression Algorithms Utilizing the QRS-wave Difference and Its Realization on the Wireless Holter System
title_full ECG Lossless/Lossy Compression Algorithms Utilizing the QRS-wave Difference and Its Realization on the Wireless Holter System
title_fullStr ECG Lossless/Lossy Compression Algorithms Utilizing the QRS-wave Difference and Its Realization on the Wireless Holter System
title_full_unstemmed ECG Lossless/Lossy Compression Algorithms Utilizing the QRS-wave Difference and Its Realization on the Wireless Holter System
title_sort ecg lossless/lossy compression algorithms utilizing the qrs-wave difference and its realization on the wireless holter system
publishDate 2013
url http://ndltd.ncl.edu.tw/handle/63307832990186486148
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