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      KCI등재 SCOPUS SCIE

      Time–frequency localization using three-tap biorthogonal wavelet fi lter bank for electrocardiogram compressions

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      https://www.riss.kr/link?id=A106841093

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      다국어 초록 (Multilingual Abstract)

      A joint time–frequency localized three-band biorthogonal wavelet fi lter bank to compress Electrocardiogram signals is proposedin this work. Further, the use of adaptive thresholding and modifi ed run-length encoding resulted in maximum datavolume r...

      A joint time–frequency localized three-band biorthogonal wavelet fi lter bank to compress Electrocardiogram signals is proposedin this work. Further, the use of adaptive thresholding and modifi ed run-length encoding resulted in maximum datavolume reduction while guaranteeing reconstructing quality. Using signal-to-noise ratio, compression ratio (C R ), maximumabsolute error (E MA ), quality score (Q s ), root mean square error, compression time (C T ) and percentage root mean squarediff erence the validity of the proposed approach is studied. The experimental results deduced that the performance of theproposed approach is better when compared to the two-band wavelet fi lter bank. The proposed compression method enablesloss-less data transmission of medical signals to remote locations for therapeutic usage.

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      참고문헌 (Reference)

      1 Al-Busaidi AM, "Wavelet-based encoding scheme for controlling size of compressed ECG segments in telecardiology systems" 41 (41): 166-, 2017

      2 Lu Z, "Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm" 47 (47): 849-856, 2000

      3 Zhao P, "Three-channel symmetric tight frame wavelet design method" 12 (12): 623-, 2013

      4 Kumar A, "Heart rate monitoring and therapeutic devices : a wavelet transform based approach for the modeling and classifi cation of congestive heart failure" 79 : 239-250, 2018

      5 Jha CK, "Electrocardiogram data compression using DCT based discrete orthogonal Stockwell transform" 46 : 174-181, 2018

      6 Wang X, "ECG compression based on combining of EMD and wavelet transform" 52 (52): 1588-1590, 2016

      7 Bhokare G, "Digital watermarking with 3-band fi lter banks" 466-470, 2008

      8 Kumar A, "Design of wavelet transform based electrocardiogram monitoring system" 80 : 381-398, 2018

      9 Bhati D, "Design of time–frequency optimal three-band wavelet fi lter banks with unit sobolev regularity using frequency domain sampling" 35 (35): 4501-4531, 2016

      10 Kumar A, "Design of a biorthogonal wavelet transform based R-peak detection and data compression scheme for implantable cardiac pacemaker systems" 42 (42): 102-, 2018

      1 Al-Busaidi AM, "Wavelet-based encoding scheme for controlling size of compressed ECG segments in telecardiology systems" 41 (41): 166-, 2017

      2 Lu Z, "Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm" 47 (47): 849-856, 2000

      3 Zhao P, "Three-channel symmetric tight frame wavelet design method" 12 (12): 623-, 2013

      4 Kumar A, "Heart rate monitoring and therapeutic devices : a wavelet transform based approach for the modeling and classifi cation of congestive heart failure" 79 : 239-250, 2018

      5 Jha CK, "Electrocardiogram data compression using DCT based discrete orthogonal Stockwell transform" 46 : 174-181, 2018

      6 Wang X, "ECG compression based on combining of EMD and wavelet transform" 52 (52): 1588-1590, 2016

      7 Bhokare G, "Digital watermarking with 3-band fi lter banks" 466-470, 2008

      8 Kumar A, "Design of wavelet transform based electrocardiogram monitoring system" 80 : 381-398, 2018

      9 Bhati D, "Design of time–frequency optimal three-band wavelet fi lter banks with unit sobolev regularity using frequency domain sampling" 35 (35): 4501-4531, 2016

      10 Kumar A, "Design of a biorthogonal wavelet transform based R-peak detection and data compression scheme for implantable cardiac pacemaker systems" 42 (42): 102-, 2018

      11 Wu FY, "Compressed acquisition and denoising recovery of EMGdi signal in WSNs and IOT" 14 (14): 2210-2219, 2018

      12 Singh A, "Block sparsity-based joint compressed sensing recovery of multi-channel ECG signals" 4 (4): 50-, 2017

      13 Kumar R, "Beta wavelet-based ECG signal compression using lossless encoding with modifi ed thresholding" 39 (39): 130-140, 2013

      14 Sharma M, "An accurate sleep stages classifi cation system using a new class of optimally timefrequency localized three-band wavelet fi lter bank" 98 : 58-75, 2018

      15 Hsieh JH, "Algorithm and VLSI architecture design of low-power SPIHT decoder for mhealth applications" 12 (12): 1450-1457, 2018

      16 Hsieh JH, "A speed-and power-effi-cient SPIHT design for wearable quality-on-demand ECG applications" 22 (22): 1456-1465, 2018

      17 Lee S, "A real-time ECG data compression and transmission algorithm for an e-health device" 58 (58): 2448-2455, 2011

      18 Miaou SG, "A quality-on-demand algorithm for waveletbased compression of electrocardiogram signals" 49 (49): 233-239, 2002

      19 Abo-Zahhad M, "A new algorithm for the compression of ECG signals based on mother wavelet parameterization and best-threshold levels selection" 23 (23): 1002-1011, 2013

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2013-10-01 평가 등재학술지 선정 (기타) KCI등재
      2010-01-01 평가 SCOPUS 등재 (기타) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.19 0.19 0.16
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.14 0.16 0.379 0.21
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