Lossless electrocardiogram signal compression: A review of existing methods

Abstract Background Cardiovascular diseases (CVDs) are among one of the leading causes of death in the world today. Electrocardiography (ECG) is commonly used to monitor and diagnose heart disorders at an early stage. In recent years, with the burgeoning of wearable technologies, portable ECGs have been applied not only for tele-health cardiac monitoring and diagnostic applications, but also for stress monitoring, fitness analysis, and general health assessment, to name a few. Such devices are capable of generating a wealth of data, but due to transmission and storage limitations, the majority of the recorded ECG data is discarded and lower-dimensional features, such as heart rate or heart rate variability, are stored instead. Devices that do allow for ECG recording/streaming, in turn, typically apply lossy compression algorithms, thus are not applicable for clinical use. While lossless compression techniques have been widely used in allied domains, limited application has been seen for ECGs. Objective This literature review aims at providing the research community a summary of lossless compression methods developed specifically for ECGs and compares existing methods based on the depth and breadth of the databases in which they were tested, the specific compression algorithms used, and how their performances were evaluated. Methods English peer-reviewed journal articles published between 1990 and 2017 were chosen as the target of this review. A data extraction sheet was then prepared to group and categorize articles to developing a better understanding of the research directions taken by the community and the important components to be taken into account while working with ECG lossless compression algorithms. Results The different articles were grouped and analyzed on the basis of the databases used, pre-processing, compression methods, type of implementation, performance measures used and comparisons with prior art. Several recommendations and research directions were provided based on the current work. Conclusion It is hoped that this review will provide technology developers with invaluable insights, thus opening doors for wearables devices with clinically-relevant capabilities.

[1]  Tiago H. Falk,et al.  Adaptive modulation spectral filtering for improved electrocardiogram quality enhancement , 2016, 2016 Computing in Cardiology Conference (CinC).

[2]  Yue-Der Lin,et al.  An Efficient Lossless ECG Compression Method Using Delta Coding and Optimal Selective Huffman Coding , 2010 .

[3]  Ericson Chua,et al.  Mixed bio-signal lossless data compressor for portable brain-heart monitoring systems , 2011, IEEE Transactions on Consumer Electronics.

[4]  Madhuchhanda Mitra,et al.  A lossless ECG data compression technique using ASCII character encoding , 2011, Comput. Electr. Eng..

[5]  Yong Lian,et al.  A low complexity lossless compression scheme for wearable ECG sensors , 2015, 2015 IEEE International Conference on Digital Signal Processing (DSP).

[6]  O. H. Schmitt,et al.  Report of committee on electrocardiography, American Heart Association. Recommendations for standardization of leads and of specifications for instruments in electrocardiography and vectorcardiography. , 1967, Circulation.

[7]  Herbert Nettlau,et al.  Electrocardiographic monitoring during marathon running: a proof of feasibility for a new telemedical approach , 2014, European journal of preventive cardiology.

[8]  S. K. Mukhopadhyay,et al.  Noise reduction and lossless ECG encoding , 2014, Proceedings of The 2014 International Conference on Control, Instrumentation, Energy and Communication (CIEC).

[9]  Shih-Lun Chen,et al.  An Asynchronous Multi-Sensor Micro Control Unit for Wireless Body Sensor Networks (WBSNs) , 2011, Sensors.

[10]  Kwang-Ting Cheng,et al.  Real-time lossless ECG compression for low-power wearable medical devices based on adaptive region prediction , 2014 .

[11]  M L Simoons,et al.  Comparison of usefulness of computer assisted continuous 48-h 3-lead with 12-lead ECG ischaemia monitoring for detection and quantitation of ischaemia in patients with unstable angina. , 1997, European heart journal.

[12]  W. A. Coberly,et al.  ECG data compression techniques-a unified approach , 1990, IEEE Transactions on Biomedical Engineering.

[13]  Willis J. Tompkins,et al.  Biomedical Digital Signal Processing , 1993 .

[14]  Chien-Hung Chen,et al.  Heart beats in the cloud: distributed analysis of electrophysiological 'Big Data' using cloud computing for epilepsy clinical research , 2014, J. Am. Medical Informatics Assoc..

[15]  Madhuchhanda Mitra,et al.  ECG signal compression using ASCII character encoding and transmission via SMS , 2013, Biomed. Signal Process. Control..

[16]  Ioan Tabus,et al.  Using contexts and R-R interval estimation in lossless ECG compression , 2002, Comput. Methods Programs Biomed..

[17]  Chih-Lung Lin,et al.  Wavelet-based ECG compression using dynamic vector quantization with tree codevectors in single codebook , 2002, IEEE Trans. Biomed. Eng..

[18]  Shih-Lun Chen,et al.  VLSI architecture of lossless ECG compression design based on fuzzy decision and optimisation method for wearable devices , 2015 .

[19]  Abdenbi Abenaou,et al.  An Efficent Lossless Compression Scheme for ECG Signal , 2016 .

[20]  K.M. Buckley,et al.  ECG data compression using cut and align beats approach and 2-D transforms , 1999, IEEE Transactions on Biomedical Engineering.

[21]  Somnath Ghosh,et al.  LOSSLESS ELECTROCARDIOGRAM COMPRESSION TECHNIQUE AND GSM BASED TELE-CARDIOLOGY APPLICATION , 2013 .

[22]  Theodor Landis,et al.  Usefulness of Ambulatory 7-Day ECG Monitoring for the Detection of Atrial Fibrillation and Flutter After Acute Stroke and Transient Ischemic Attack , 2004, Stroke.

[23]  Haibin Shen,et al.  A dual-mode ECG processor with difference-insensitive QRS detection and lossless compression , 2017, IEICE Electron. Express.

[24]  Ting-Lan Lin,et al.  Efficient fuzzy-controlled and hybrid entropy coding strategy lossless ECG encoder VLSI design for wireless body sensor networks , 2013 .

[25]  Ziya Arnavut,et al.  ECG Signal Compression Based on Burrows-Wheeler Transformation and Inversion Ranks of Linear Prediction , 2007, IEEE Transactions on Biomedical Engineering.

[26]  Chun-Huat Heng,et al.  A Hybrid Data Compression Scheme for Power Reduction in Wireless Sensors for IoT , 2017, IEEE Transactions on Biomedical Circuits and Systems.

[27]  G. Moody,et al.  The European ST-T database: standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography. , 1992, European heart journal.

[28]  Qunyi Zhou,et al.  Study on ECG Data Lossless Compression Algorithm Based on K-means Cluster , 2009, 2009 ETP International Conference on Future Computer and Communication.

[29]  Ju Wang,et al.  VLSI implementation of low-power cost-efficient lossless ECG encoder design for wireless healthcare monitoring application , 2013 .

[30]  Francesco Marcelloni,et al.  Reducing Power Consumption in Wireless Sensor Networks Using a Novel Approach to Data Aggregation , 2008, Comput. J..

[31]  J. S. Sahambi,et al.  Lossless ECG Compression for Event Recorder Based on Burrows-Wheeler Transformation and Move-To-Front Coder , 2009 .

[32]  Chun-Huat Heng,et al.  A 3-Lead ECG-on-Chip with QRS Detection and Lossless Compression for Wireless Sensors , 2016, IEEE Transactions on Circuits and Systems II: Express Briefs.

[33]  Francesco Marcelloni,et al.  An Efficient Lossless Compression Algorithm for Tiny Nodes of Monitoring Wireless Sensor Networks , 2009, Comput. J..

[34]  Federico Lecumberry,et al.  Efficient Sequential Compression of Multichannel Biomedical Signals , 2016, IEEE Journal of Biomedical and Health Informatics.

[35]  Dong-Sun Kim,et al.  A Lossless Multichannel Bio-Signal Compression Based on Low-Complexity Joint Coding Scheme for Portable Medical Devices , 2014, Sensors.

[36]  Roger G. Mark,et al.  Evaluation of the 'TRIM' ECG data compressor , 1988, Proceedings. Computers in Cardiology 1988.

[37]  G. M. Baule,et al.  Research in electrocardiography and magnetocardiography , 1972 .

[38]  Dilbag Singh,et al.  Ectopic beats in approximate entropy and sample entropy-based HRV assessment , 2012, Int. J. Syst. Sci..

[39]  Tomasz P. Zielinski,et al.  Lossless ECG compression with lifting wavelet transform , 2001, IMTC 2001. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference. Rediscovering Measurement in the Age of Informatics (Cat. No.01CH 37188).

[40]  C Zywietz,et al.  Common Standards for Quantitative Electrocardiography: Goals and Main Results , 1990, Methods of Information in Medicine.

[41]  Yong Lian,et al.  A Joint QRS Detection and Data Compression Scheme for Wearable Sensors , 2015, IEEE Transactions on Biomedical Engineering.

[42]  Arnon D. Cohen,et al.  The weighted diagnostic distortion (WDD) measure for ECG signal compression , 2000, IEEE Transactions on Biomedical Engineering.

[43]  M. Fereniec,et al.  Wavelet Denoising for Multi-lead High Resolution ECG Signals , 2007 .

[44]  P. Johnston,et al.  Origin of the electrocardiogram , 1994, IEEE Engineering in Medicine and Biology Magazine.

[45]  Hong Wang,et al.  The history, hotspots, and trends of electrocardiogram , 2015, Journal of geriatric cardiology : JGC.

[46]  Khalid Sayood,et al.  Introduction to Data Compression , 1996 .

[47]  Yong Lian,et al.  An ECG-on-Chip With 535 nW/Channel Integrated Lossless Data Compressor for Wireless Sensors , 2014, IEEE Journal of Solid-State Circuits.

[48]  Shaou-Gang Miaou,et al.  Wavelet-based lossy-to-lossless ECG compression in a unified vector quantization framework , 2005, IEEE Transactions on Biomedical Engineering.

[49]  M. Sabarimalai Manikandan,et al.  Wavelet-based electrocardiogram signal compression methods and their performances: A prospective review , 2014, Biomed. Signal Process. Control..

[50]  Shih-Lun Chen,et al.  An Efficient Micro Control Unit with a Reconfigurable Filter Design for Wireless Body Sensor Networks (WBSNs) , 2012, Sensors.

[51]  Abdenbi Abenaou,et al.  An enhanced method of lossless ECG data compression using ASCII character encoding , 2014, 2014 Second World Conference on Complex Systems (WCCS).

[52]  O Pahlm,et al.  Compact digital storage of ECG's. , 1979, Computer programs in biomedicine.

[53]  A. Houghton,et al.  MAKING SENSE OF THE ECG A HANDS-ON GUIDE , 2008 .

[54]  Piotr Augustyniak.  Transform-based reduction of inter-channel correlation applied to lossless coding of multichannel ECG , 2001, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[55]  Ramakrishnan Kannan,et al.  Lossless Compression Schemes for ECG Signals Using Neural Network Predictors , 2007, EURASIP J. Adv. Signal Process..

[56]  A Koski,et al.  Lossless ECG encoding. , 1997, Computer methods and programs in biomedicine.

[57]  G.B. Moody,et al.  The impact of the MIT-BIH Arrhythmia Database , 2001, IEEE Engineering in Medicine and Biology Magazine.

[58]  Hiroyoshi Morita,et al.  On-Line Electrocardiogram Lossless Compression Using Antidictionary Codes for a Finite Alphabet , 2010, IEICE Trans. Inf. Syst..