PMID- 26846671
OWN - NLM
STAT- MEDLINE
DCOM- 20170109
LR  - 20170110
IS  - 1872-7565 (Electronic)
IS  - 0169-2607 (Linking)
VI  - 129
DP  - 2016 Jun
TI  - Hybrid method based on singular value decomposition and embedded zero tree 
      wavelet technique for ECG signal compression.
PG  - 135-48
LID - S0169-2607(15)30119-X [pii]
LID - 10.1016/j.cmpb.2016.01.006 [doi]
AB  - BACKGROUND AND OBJECTIVE: In the field of biomedical, it becomes necessary to 
      reduce data quantity due to the limitation of storage in real-time ambulatory 
      system and telemedicine system. Research has been underway since very beginning 
      for the development of an efficient and simple technique for longer term 
      benefits. METHOD: This paper, presents an algorithm based on singular value 
      decomposition (SVD), and embedded zero tree wavelet (EZW) techniques for ECG 
      signal compression which deals with the huge data of ambulatory system. The 
      proposed method utilizes the low rank matrix for initial compression on two 
      dimensional (2-D) ECG data array using SVD, and then EZW is initiated for final 
      compression. Initially, 2-D array construction has key issue for the proposed 
      technique in pre-processing. Here, three different beat segmentation approaches 
      have been exploited for 2-D array construction using segmented beat alignment 
      with exploitation of beat correlation. The proposed algorithm has been tested on 
      MIT-BIH arrhythmia record, and it was found that it is very efficient in 
      compression of different types of ECG signal with lower signal distortion based 
      on different fidelity assessments. RESULTS: The evaluation results illustrate 
      that the proposed algorithm has achieved the compression ratio of 24.25:1 with 
      excellent quality of signal reconstruction in terms of percentage-root-mean 
      square difference (PRD) as 1.89% for ECG signal Rec. 100 and consumes only 162bps 
      data instead of 3960bps uncompressed data. CONCLUSION: The proposed method is 
      efficient and flexible with different types of ECG signal for compression, and 
      controls quality of reconstruction. Simulated results are clearly illustrate the 
      proposed method can play a big role to save the memory space of health data 
      centres as well as save the bandwidth in telemedicine based healthcare systems.
CI  - Copyright (c) 2016 Elsevier Ireland Ltd. All rights reserved.
FAU - Kumar, Ranjeet
AU  - Kumar R
AD  - PDPM Indian Institute of Information Technology, Design and Manufacturing 
      Jabalpur, Jabalpur 482005, India. Electronic address: ranjeet281@gmail.com.
FAU - Kumar, A
AU  - Kumar A
AD  - PDPM Indian Institute of Information Technology, Design and Manufacturing 
      Jabalpur, Jabalpur 482005, India. Electronic address: anilkdee@gmail.com.
FAU - Singh, G K
AU  - Singh GK
AD  - Department of Electrical Engineering, Indian Institute of Technology Roorkee, 
      Roorkee 247667, Uttarakhand, India. Electronic address: gksngfee@gmail.com.
LA  - eng
PT  - Journal Article
DEP - 20160118
PL  - Ireland
TA  - Comput Methods Programs Biomed
JT  - Computer methods and programs in biomedicine
JID - 8506513
SB  - IM
MH  - Algorithms
MH  - Arrhythmias, Cardiac/physiopathology
MH  - Electrocardiography/*methods
MH  - Humans
OTO - NOTNLM
OT  - ECG compression
OT  - EZW
OT  - Healthcare
OT  - SVD
OT  - Telemedicine
OT  - Wavelet
EDAT- 2016/02/06 06:00
MHDA- 2017/01/10 06:00
CRDT- 2016/02/06 06:00
PHST- 2015/08/19 00:00 [received]
PHST- 2015/12/31 00:00 [revised]
PHST- 2016/01/05 00:00 [accepted]
PHST- 2016/02/06 06:00 [entrez]
PHST- 2016/02/06 06:00 [pubmed]
PHST- 2017/01/10 06:00 [medline]
AID - S0169-2607(15)30119-X [pii]
AID - 10.1016/j.cmpb.2016.01.006 [doi]
PST - ppublish
SO  - Comput Methods Programs Biomed. 2016 Jun;129:135-48. doi: 
      10.1016/j.cmpb.2016.01.006. Epub 2016 Jan 18.