Review of Energy Efficient Factors for ECG Devices

Many embedded devices have been proposed and implemented for long term Electrocardiogram (ECG) monitoring which can be either a recording system only used to acquire, store and transmit signals while consuming huge energy or an analyzing system which detects and extract required information and transmits this information but does not retain signals/time history for further diagnosis. Long term monitoring devices need a hybrid of both these systems. The architecture and design of long term ECG monitoring devices is a trade-off of a number of intertwined factors not limited to user convenience (lightweight, non-interference with day to day activities, free movement), Energy efficiency, reliability and cost while ensuring safety. However, all long-term ECG monitoring devices fundamentally need to have an embedded effective and efficient filtering and detection scheme which ensures high reliability of detection and energy efficiency. This paper surveys and summarizes primary research work in the area of filtering and detection of ECG signals in the context of reliable and energy efficient long term ECG monitoring. Key-Words: ECG monitoring, ECG analysis, Energy efficiency, Transmission, Filtering, Detection, Denoising, Ventricular fibrillation

[1]  W.J. Tompkins,et al.  Neural-network-based adaptive matched filtering for QRS detection , 1992, IEEE Transactions on Biomedical Engineering.

[2]  Guy Carrault,et al.  Real-time ECG transmission via Internet for nonclinical applications , 2001, IEEE Transactions on Information Technology in Biomedicine.

[3]  Ting Jiang,et al.  Compressed Sensing Based on the Characteristic Correlation of ECG in Hybrid Wireless Sensor Network , 2015, Int. J. Distributed Sens. Networks.

[4]  Jean-Michel Morel,et al.  A non-local algorithm for image denoising , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[5]  Lui Sha,et al.  A Medical-Grade Wireless Architecture for Remote Electrocardiography , 2011, IEEE Transactions on Information Technology in Biomedicine.

[6]  Steffen Leonhardt,et al.  Validating the Reliability of Five Ventricular Fibrillation Detecting Algorithms , 2009 .

[7]  Qiao Li,et al.  Ventricular Fibrillation and Tachycardia Classification Using a Machine Learning Approach , 2014, IEEE Transactions on Biomedical Engineering.

[8]  Jungyoon Kim,et al.  ETD: An extended time delay algorithm for ventricular fibrillation detection , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  Shuenn-Yuh Lee,et al.  Low-Power Wireless ECG Acquisition and Classification System for Body Sensor Networks , 2015, IEEE Journal of Biomedical and Health Informatics.

[10]  R. Poli,et al.  Genetic design of optimum linear and nonlinear QRS detectors , 1995, IEEE Transactions on Biomedical Engineering.

[11]  Hamid Sharif,et al.  Assurance of Energy Efficiency and Data Security for ECG Transmission in BASNs , 2012, IEEE Transactions on Biomedical Engineering.

[12]  Paulo Carvalho,et al.  Detection of Atrial Fibrillation using model-based ECG analysis , 2008, 2008 19th International Conference on Pattern Recognition.

[13]  Shuenn-Yuh Lee,et al.  A wireless electrocardiogram detection for personal health monitoring , 2013, 2013 1st International Conference on Orange Technologies (ICOT).

[14]  Liviu Goras,et al.  An ECG Signals Compression Method and Its Validation Using NNs , 2008, IEEE Transactions on Biomedical Engineering.

[15]  Prabin Kumar Bora,et al.  Electrocardiogram signal denoising using non-local wavelet transform domain filtering , 2015, IET Signal Process..

[16]  José Luis Rojo-Álvarez,et al.  Detection of Life-Threatening Arrhythmias Using Feature Selection and Support Vector Machines , 2014, IEEE Transactions on Biomedical Engineering.

[17]  Kenneth E. Barner,et al.  A weighted ℓ1 minimization algorithm for compressed sensing ECG , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[18]  Seema,et al.  Comparison of different approaches for removal of baseline wander from ECG signal , 2011, ICWET.

[19]  Luca Citi,et al.  A Real-Time Automated Point-Process Method for the Detection and Correction of Erroneous and Ectopic Heartbeats , 2012, IEEE Transactions on Biomedical Engineering.

[20]  Jaya Prakash Sahoo,et al.  Analysis of ECG signal for Detection of Cardiac Arrhythmias , 2011 .

[21]  Pablo Laguna,et al.  Block adaptive filters with deterministic reference inputs for event-related signals: BLMS and BRLS , 2002, IEEE Trans. Signal Process..

[22]  H. B. Riley,et al.  Performance Study of Different Denoising Methods for ECG Signals , 2014, EUSPN/ICTH.

[23]  Charles Sodini,et al.  A long-term wearable electrocardiogram measurement system , 2013, 2013 IEEE International Conference on Body Sensor Networks.

[24]  Sridhar Krishnan,et al.  Reconstruction of ECG signals for compressive sensing by promoting sparsity on the gradient , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[25]  R. Orglmeister,et al.  The principles of software QRS detection , 2002, IEEE Engineering in Medicine and Biology Magazine.

[26]  Celia Shahnaz,et al.  Denoising of ECG signals based on noise reduction algorithms in EMD and wavelet domains , 2012, Biomed. Signal Process. Control..

[27]  Ataollah Ebrahimzadeh,et al.  Detection of electrocardiogram signals using an efficient method , 2014, Appl. Soft Comput..

[28]  Alexander Schlaefer,et al.  A Fast Lane Approach to LMS prediction of respiratory motion signals , 2008, Biomed. Signal Process. Control..

[29]  Samarendra Dandapat,et al.  Multilead ECG data compression using SVD in multiresolution domain , 2016, Biomed. Signal Process. Control..

[30]  M. P. Parsai,et al.  Comparative Analysis of Various Wavelet Families used for R-Wave Detection of ECG Waveforms , 2013 .

[31]  H Nagendra,et al.  Application of Wavelet Techniques in ECG Signal Processing: An Overview , 2011 .

[32]  Celia Shahnaz,et al.  An ECG signal denoising method based on enhancement algorithms in EMD and Wavelet domains , 2011, TENCON 2011 - 2011 IEEE Region 10 Conference.

[33]  Jun Zhang,et al.  Energy-Efficient ECG Compression on Wireless Biosensors via Minimal Coherence Sensing and Weighted $\ell_1$ Minimization Reconstruction , 2015, IEEE Journal of Biomedical and Health Informatics.

[34]  A. Amann,et al.  Reliability of old and new ventricular fibrillation detection algorithms for automated external defibrillators , 2005, Biomedical engineering online.

[35]  Mohammed Tarique,et al.  REAL TIME WIRELESS HEALTH MONITORING APPLICATION USING MOBILE DEVICES , 2015 .

[36]  Khaled Daqrouq,et al.  ECG Signal Denoising By Wavelet Transform Thresholding , 2008 .

[37]  Eric L. Miller,et al.  Nonlocal Means Denoising of ECG Signals , 2012, IEEE Transactions on Biomedical Engineering.

[38]  Mathias Wilhelms,et al.  In Silico Investigation of Electrically Silent Acute Cardiac Ischemia in the Human Ventricles , 2011, IEEE Transactions on Biomedical Engineering.

[39]  Jusak Jusak,et al.  Wireless tele-auscultation for phonocardiograph signal recording through Zigbee networks , 2015, 2015 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob).

[40]  A. Ruha,et al.  A real-time microprocessor QRS detector system with a 1-ms timing accuracy for the measurement of ambulatory HRV , 1997, IEEE Transactions on Biomedical Engineering.

[41]  Yongqin Li,et al.  An Algorithm Used for Ventricular Fibrillation Detection Without Interrupting Chest Compression , 2012, IEEE Transactions on Biomedical Engineering.

[42]  Salim Lahmiri,et al.  Comparative study of ECG signal denoising by wavelet thresholding in empirical and variational mode decomposition domains. , 2014, Healthcare technology letters.

[43]  Álvaro Alesanco Iglesias,et al.  Clinical Assessment of Wireless ECG Transmission in Real-Time Cardiac Telemonitoring , 2010, IEEE Transactions on Information Technology in Biomedicine.

[44]  Rajarshi Gupta,et al.  Delineation of ECG characteristic features using multiresolution wavelet analysis method , 2012 .

[45]  Manuel Blanco-Velasco,et al.  ECG signal denoising and baseline wander correction based on the empirical mode decomposition , 2008, Comput. Biol. Medicine.

[46]  Pablo Laguna,et al.  A robust method for ECG-based estimation of the respiratory frequency during stress testing , 2006, IEEE Transactions on Biomedical Engineering.

[47]  Celia Shahnaz,et al.  COMPARISON OF ECG SIGNAL DENOISING ALGORITHMS IN EMD AND WAVELET DOMAINS , 2012 .

[48]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[49]  C. Li,et al.  Detection of ECG characteristic points using wavelet transforms. , 1995, IEEE transactions on bio-medical engineering.

[50]  Adel Belouchrani,et al.  QRS detection based on wavelet coefficients , 2012, Comput. Methods Programs Biomed..

[51]  Kapil Tajane,et al.  Review Paper :Comparative Analysis Of Mother Wavelet Functions With The ECG Signals , 2014 .

[52]  Logan Porter.  Wireless in-home ECG monitoring system with remote access , 2012 .

[53]  A. G. Ramakrishnan,et al.  Threshold-Independent QRS Detection Using the Dynamic Plosion Index , 2014, IEEE Signal Processing Letters.

[54]  Xiaojun Yuan,et al.  Multiple Functional ECG Signal is Processing for Wearable Applications of Long-Term Cardiac Monitoring , 2011, IEEE Transactions on Biomedical Engineering.

[55]  Björn Eskofier,et al.  Wearable real-time ecg monitoring with emergency alert system for scuba diving , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[56]  P. C. Cortez,et al.  An innovative approach of QRS segmentation based on first-derivative, Hilbert and Wavelet Transforms. , 2012, Medical engineering & physics.

[57]  Basabi Bhaumik,et al.  An Energy Efficient ECG Signal Processor Detecting Cardiovascular Diseases on Smartphone , 2017, IEEE Transactions on Biomedical Circuits and Systems.

[58]  Koushik Maharatna,et al.  Design of a Low-Power On-Body ECG Classifier for Remote Cardiovascular Monitoring Systems , 2013, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[59]  Yuanjin Zheng,et al.  A real-time ECG QRS detection ASIC based on wavelet multiscale analysis , 2009, 2009 IEEE Asian Solid-State Circuits Conference.

[60]  Ernano Arrais Junior,et al.  Real Time QRS Detection Based on Redundant Discrete Wavelet Transform , 2016, IEEE Latin America Transactions.

[61]  Arnon D. Cohen,et al.  ECG signal compression using analysis by synthesis coding , 2000, IEEE Transactions on Biomedical Engineering.

[62]  Sever Pasca,et al.  A WBAN-ECG approach for real-time long-term monitoring , 2013, 2013 8TH INTERNATIONAL SYMPOSIUM ON ADVANCED TOPICS IN ELECTRICAL ENGINEERING (ATEE).

[63]  Paul S Addison,et al.  Wavelet transforms and the ECG: a review , 2005, Physiological measurement.

[64]  M. Z. U. Rahman,et al.  Efficient and Simplified Adaptive Noise Cancelers for ECG Sensor Based Remote Health Monitoring , 2012, IEEE Sensors Journal.

[65]  Shan Huang,et al.  An Energy-Efficient Design for ECG Recording and R-Peak Detection Based on Wavelet Transform , 2015, IEEE Transactions on Circuits and Systems II: Express Briefs.

[66]  Jung-Yoon Kim,et al.  Analysis of energy consumption for wearable ECG devices , 2014, IEEE SENSORS 2014 Proceedings.

[67]  A. Amann,et al.  A new ventricular fibrillation detection algorithm for automated external defibrillators , 2005, Computers in Cardiology, 2005.

[68]  Szi-Wen Chen,et al.  A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising , 2006, Comput. Methods Programs Biomed..

[69]  Shamim Nemati,et al.  Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters , 2015, IEEE Transactions on Biomedical Engineering.

[70]  Sabir Jacquir,et al.  Automatic detection of P, QRS and T patterns in 12 leads ECG signal based on CWT , 2016, Biomed. Signal Process. Control..

[71]  L. Sornmo,et al.  Block LMS adaptive filter with deterministic reference inputs for event-related signals , 2001, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[72]  Li Bin,et al.  A system of portable ECG monitoring based on Bluetooth mobile phone , 2011, 2011 IEEE International Symposium on IT in Medicine and Education.

[73]  Pierre Vandergheynst,et al.  Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor Nodes , 2011, IEEE Transactions on Biomedical Engineering.

[74]  Murugappan Murugappan,et al.  ECG Signal Denoising Using Wavelet Thresholding Techniques in Human Stress Assessment , 2012 .

[75]  N.V. Thakor,et al.  Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection , 1991, IEEE Transactions on Biomedical Engineering.

[76]  Rui Paulo Martins,et al.  A 0.83-µW QRS Detection Processor Using Quadratic Spline Wavelet Transform for Wireless ECG Acquisition in 0.35-µm CMOS , 2012, IEEE Trans. Biomed. Circuits Syst..