Abstract
With the alarming rise in deaths due to cardiovascular diseases (CVD), the present medical research scenario emphasizes techniques and methods to detect CVDs. As the world health organization adduced, technological proceeds in cardiac function assessment have become the nucleus and heart of all leading research studies on CVDs. Electrocardiogram (ECG) analysis is the most functional and convenient tool used to test the range of heart-related irregularities. Most of the approaches present in the literature on ECG signal analysis consider noise removal, rhythm-based analysis, and heartbeat detection to improve the performance of a cardiac pacemaker. Advancements in ECG segment detection and beat classification have a limited evaluation and still require clinical approvals. This chapter discusses approachesĀ and techniques to implement an on-chip ECG detector for a cardiac pacemaker system. Moreover, different challenges regarding the ECG signal morphology analysis deriving from the medical literature are extensively reviewed.
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References
Acharya UR, Fujita H, Lih OS, Hagiwara Y, Tan JH, Adam M (2017) Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network. Inf Sci 405:81ā90
Adnane M, Jiang Z, Choi S (2009) Development of QRS detection algorithm designed for wearable cardiorespiratory system. Comput Methods Programs Biomed 93(1):20ā31
Afonso VX, Tompkins WJ, Nguyen TQ, Luo S (1999) ECG beat detection using filter banks. IEEE Trans Biomed Eng 46(2):192ā202
Ansari-Ram, F, Hosseini-Khayat S (2012) ECG signal compression using compressed sensing with nonuniform binary matrices. In: 2012 16th CSI International Symposium on artificial intelligence and signal processing (AISP). IEEE, pp 305ā309
Azmoudeh B, Cvetkovic D (2014) Wavelets in Biomedical signal processing and analysis. Encycl Biomed Eng 193ā212
Baek HJ, Chung GS, Kim KK, Park KS (2012) A smart health monitoring chair for nonintrusive measurement of biological signals. IEEE Trans Inf Technol Biomed 16(1):150ā158
Bahoura M, Hassani M, Hubin M (1997) DSP implementation of wavelet transform for real time ECG wave forms detection and heartrate analysis. Comput Methods Programs Biomed 52(1):35ā44
Banerjee S, Mitra M (2014) Application of cross wavelet transform for ECG pattern analysis and classification. IEEE Trans Instrum Meas 63(2):326ā333
Barro S, Fernandez-Delgado M, Vila-Sobrino JA, Regueiro CV, Sanchez E (1998) Classifying multichannel ECG patterns with an adaptive neural network. IEEE Eng Med Biol Mag 17(1):45ā55
Belkadi MA, Daamouche A (2021) A robust QRS detection approach using stationary wavelet transform. Multimedia Tools Appl 1ā22. https://doi.org/10.1007/S11042-020-10500-9
Benmalek M, Charef A (2009) Digital fractional order operators for R-wave detection in electrocardiogram signal. IET Signal Proc 3(5):381ā391
Berkaya SK, Uysal AK, Gunal ES, Ergin S, Gunal S, Gulmezoglu MB (2018) A survey on ECG analysis. Biomed Signal Process Control 43:216ā235
Bhavtosh, Berwal D, Kumar, Y (2015) High performance QRS complex detector for wearable ECG systems using Multi Scaled product with booth multiplier and soft threshold algorithm. In: 2015 international conference on signal processing and communication (ICSC), pp 204ā209. IEEE
Bono V, Mazomenos EB, Chen T, Rosengarten JA, Acharyya A, Maharatna K, Morgan JM, Curzen N (2014) Development of an automated updated Selvester QRS scoring system using SWT-based QRS fractionation detection and classification. IEEE J Biomed Health Inform 18(1):193ā204
Capurro I, Lecumberry F, MartĆn A, RamĆrez I, Rovira E, Seroussi G (2017) Efficient sequential compression of multichannel biomedical signals. IEEE J Biomed Health Inform 21(4):904ā916
Casson AJ, Rodriguez-Villegas E (2012) Signal agnostic compressive sensing for body area networks: Comparison of signal reconstructions. In: 2012 Annual international conference of the IEEE engineering in medicine and biology society (EMBC). IEEE, pp 4497ā4500
Chae DH, Alem YF, Durrani S, Kennedy RA (2013) Performance study of compressive sampling for ECG signal compression in noisy and varying sparsity acquisition. In ICASSP, pp 1306ā1309
Chang MC, Lin ZX, Chang CW, Chan HL, Feng WS (2004) Design of a system-on-chip for ECG signal processing. In: The 2004 IEEE Asia-Pacific conference on circuits and systems, 2004. Proceedings, vol. 1. IEEE, pp 441ā444
Chen SL, Wang JG (2013) VLSI implementation of low-power cost-efficient lossless ECG encoder design for wireless healthcare monitoring application. Electron Lett 49(2):91ā93
Chen SL, Lee HY, Chen CA, Huang HY, Luo CH (2009) Wireless body sensor network with adaptive low-power design for biometrics and healthcare applications. IEEE Syst J 3(4):398ā409
Chen SW, Chen HC, Chan HL (2006) A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising. Comput Methods Programs Biomed 82(3):187ā195
Chiarugi F, Sakkalis V, Emmanouilidou D, Krontiris T, Varanini M, Tollis I (2007) Adaptive threshold QRS detector with best channel selection based on a noise rating system. In: Computers in cardiology. IEEE, pp 157ā160
Chouhan VS, Mehta SS (2008) Detection of QRS complexes in 12-lead ECG using adaptive quantized threshold. Int J Comput Sci Netw Secur 8(1):155ā163
Chua E, Fang WC (2011) Mixed bio-signal lossless data compressor for portable brain-heart monitoring systems. IEEE Trans Consum Electron 57(1):267ā273
Cocherova E, Surda J, Pucik J, Stofanik V (2009) Dependence of the RF field absorption on the human body dimensions. In: 19th International conference Radioelektronika, RADIOELEKTRONIKAā09. IEEE, pp 327ā329
Craven D, McGinley B, Kilmartin L, Glavin M, Jones E (2017) Adaptive dictionary reconstruction for compressed sensing of ECG signals. IEEE J Biomed Health Inform 21(3):645ā654
Deepu CJ, Lian Y (2015) A joint QRS detection and data compression Technique for wearable sensors. IEEE Trans Biomed Eng 62(1):165ā175
Deepu CJ, Heng CH, Lian Y (2017) A hybrid data compression technique for power reduction in wireless sensors for IoT. IEEE Trans Biomed Circuits Syst 11(2):245ā254
Deepu CJ, Zhang X, Liew WS, Wong DLT, Lian Y (2013) An ECG-SoC with 535nW/channel lossless data compression for wearable sensors. In: 2013 IEEE Asian solid-state circuits conference (A-SSCC). IEEE, pp 145ā148
Delano MK, Sodini CG (2013) A long-term wearable electrocardiogram measurement system. In: 2013 IEEE international conference on body sensor networks (BSN). IEEE, pp 1ā6
Der L, Razavi B (2003) A 2-GHz CMOS image-reject receiver with LMS calibration. IEEE J Solid-State Circuits 38(2):167ā175
Dinh HAN, Kumar DK, Pah ND, Burton P (2001) Wavelets for QRS detection. Australasian Phys Eng Sci Med 24(4):207
Donoho DL (1995) Denoising by soft-thresholding. IEEE Trans Inf Theory 41(3):613ā627
Elgendi M, Eskofier B, Dokos S, Abbott D (2014) Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems. PLoS ONE 9(1):e84018
Elgendi M, Mohamed A, Ward R (2017) Efficient ECG compression and QRS detection for E-health applications. Sci Rep 7(1):459
Faezipour M, Saeed A, Bulusu SC, Nourani M, Minn H, Tamil L (2010) A patient-adaptive profiling technique for ECG beat classification. IEEE Trans Inf Technol Biomed 14(5):1153ā1165
Farhang-Boroujeny B (2013) Adaptive filters: theory and applications. Wiley
Getreuer P (2006) Filter coefficients to popular wavelets. MATLAB Central
Ghaffari A, Golbayani H, Ghasemi M (2008) A new mathematical based QRS detector using continuous wavelet transform. Comput Electr Eng 34(2):81ā91
Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng CK, Stanley HE (2000) PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101(23):e215āe220
Gutta S, Cheng Q (2016) Joint feature extraction and classifier design for ECG-based biometric recognition. IEEE J Biomed Health Inform 20(2):460ā468
Hong JH, Lee SY, Liang MC, Hsieh CH, Chien SYC (2013). A wireless ECG acquisition and classification system for body sensor networks. In: 2013 35th Annual international conference of the IEEE engineering in medicine and biology society (EMBC). IEEE, pp 5183ā5186
Hooshmand M, Zordan D, Del Testa D, Grisan E, Rossi M (2017) Boosting the battery life of wearables for health monitoring through the compression of biosignals. IEEE Internet Things J 4(5):1647ā1662
Hou Z, Dong Y, Xiang J, Li X, Yang B (2018) A real-time QRS detection method based on phase portraits and box-scoring calculation. IEEE Sens J 18(9):3694ā3702
Hu YH, Tompkins WJ, Urrusti JL, Afonso VX (1993) Applications of artificial neural networks for ECG signal detection and classification. J Electrocardiol 26:66ā73
Huang P (2018) Study on a low-complexity ECG compression technique with two-tier sensors. IEEE Trans Very Large-Scale Integr (VLSI) Syst 99:1ā5
Ieong CI, Mak PI, Lam CP, Dong C, Vai MI, Mak PU, Pun SH, Wan F, Martins RP (2012) A 0.83-QRS detection processor using quadratic spline wavelet transform for wireless ECG acquisition in 0.35-CMOS. IEEE Trans Biomed Circuits Syst 6(6):586ā595
Jager F, Taddei A, Moody GB, Emdin M, AntoliÄ G, Dorn R, Smrdel A, Marchesi C, Mark RG (2003) Long-term ST database: a reference for the development and evaluation of automated ischaemia detectors and for the study of the dynamics of myocardial ischaemia. Med Biol Eng Compu 41(2):172ā182
Jain S, Kumar A, Bajaj V (2016) Technique for QRS complex detection using particle swarm optimisation. IET Sci Meas Technol 10(6):626ā636
Jang SW, Lee SH (2021) Detection of ventricular fibrillation using wavelet transform and phase space reconstruction from ECG aignals. J Mech Med Biol 21(09):2140036
JosĆ© M (2010) Sigma-delta modulators: tutorial overview, design guide, and state-of-the-art survey. IEEE Trans Circuits Syst I Regul Pap 58(1):1ā21
Junior EA, de Medeiros Valentim RA, Brandao GB (2016) Real time QRS detection based on redundant discrete wavelet transform. IEEE Latin Am Trans 14(4):1662ā1668
Kadambe S, Murray R, Boudreaux-Bartels GF (1999) Wavelet transform-based QRS complex detector. IEEE Trans Biomed Eng 46(7):838ā848
Kay SM, Gabriel JR (2003) An invariance property of the generalized likelihood ratio test. IEEE Signal Process Lett 10(12):352ā355
Khayatzadeh M, Zhang X, Tan J, Liew WS, Lian Y (2012) A 0.7-V 17.4-Ī¼W 3-LeadWireless ECG SoC. IEEE BioCAS-2012, Nov 2012, pp 344ā47
Khaustov A, Nemati S, Clifford GD (2008) An open-source standard T-wave alternans detector for benchmarking. In: 2008 computers in cardiology. IEEE, pp 509ā512
Kim KH, Kim SJ (2003) A wavelet-based method for action potential detection from extracellular neural signal recording with low signal-to-noise ratio. IEEE Trans Biomed Eng 50(8):999ā1011
Kiranyaz S, Ince T, Gabbouj M (2016) Real-time patient-specific ECG classification by 1-D convolutional neural networks. IEEE Trans Biomed Eng 63(3):664ā675
Kohler BU, Hennig C, Orglmeister R (2002) The principles of software QRS detection. IEEE Eng Med Biol Mag 21(1):42ā57
Kumar A, Berwal D, Kumar Y (2018a) Design of high-performance ECG detector for implantable cardiac pacemaker systems using biorthogonal wavelet transform. Circuits Syst Signal Process 1ā20
Kumar A, Komaragiri R, Kumar M (2018b) From pacemaker to wearable: techniques for ECG detection systems. J Med Syst 42(2):34
Kumar R, Kumar A, Pandey RK (2013) Beta wavelet-based ECG signal compression using lossless encoding with modified thresholding. Comput Electr Eng 39(1):130ā140
Kumaravel N, Nithiyanandam N (1998) Genetic-algorithm cancellation of sinusoidal powerline interference in electrocardiograms. Med Biol Eng Compu 36(2):191ā196
Kuo TH, Chen KD, Chen JR (1999) Automatic coefficients design for high-order sigma-delta modulators. IEEE Trans Circuits Syst II: Analog Digit Signal Process 46(1):6ā15
Kyrkos A, Giakoumakis EA, Carayannis G (1988) QRS detection through time recursive prediction techniques. Signal Process 15(4):429ā436
Laguna P, Mark RG, Goldberg A, Moody GB (1997) A database for evaluation of algorithms for measurement of QT and other waveform intervals in the ECG. In: Computers in cardiology. IEEE, pp 673ā676
Lee HJ, Hwang SH, Lee SM, Lim YG, Park KS (2013) Estimation of body postures on bed using unconstrained ECG measurements. IEEE J Biomed Health Inform 17(6):985ā993
Lee SY, Hong JH, Hsieh CH, Liang MC, Chien SYC, Lin KH (2015) Low-power wireless ECG acquisition and classification system for body sensor networks. IEEE J Biomed Health Inform 19(1):236ā246
Li C, Zheng C, Tai C (1995) Detection of ECG characteristic points using wavelet transforms. IEEE Trans Biomed Eng 42(1):21ā28
Lin KP, Chang WH (1989) QRS feature extraction using linear prediction. IEEE Trans Biomed Eng 36(10):1050ā1055
Lin SY, Lin HT, Lin YY (2018) Lossless and lossy direct compression design with multi-signal symptom detection for low-temperature wearable devices. IEEE Sens J
Liu X, Zheng Y, Phyu MW, Zhao B, Je M, Yuan X (2011) Multiple functional ECG signal is processing for wearable applications of long-term cardiac monitoring. IEEE Trans Biomed Eng 58(2):380ā389
Luk W, Jones G (1987) Systolic arrays for recursive digital filtering. Electron Lett 23(22):1174ā1175
Ma Y, Li T, Ma Y, Zhan K (2016) Novel real-time FPGA-based R-wave detection using lifting wavelet. Circ Syst Signal Process 35(1):281ā299
Mahmoodabadi SZ, Ahmadian A, Abolhasani MD, Eslami M, Bidgoli JH (2006) ECG feature extraction based on multiresolution wavelet transform. In: 27th Annual international conference of the engineering in medicine and biology society, 2005. IEEE-EMBS 2005. IEEE, pp 3902ā3905
Mallat SG (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7):674ā693
Mamaghanian H, Khaled N, Atienza D, Vandergheynst P (2011) Compressed sensing for real-time energy-efficient ECG compression on wireless body sensor nodes. IEEE Trans Biomed Eng 58(9):2456ā2466
Manikandan MS, Dandapat S (2007) Wavelet-based ECG and PCG signals compression technique for mobile telemedicine. In: International conference on advanced computing and communications, 2007. ADCOM 2007. IEEE, pp 164ā169
Martin-Clemente R, Camargo-Olivares JL, Hornillo-Mellado S, Elena M, Roman I (2011) Fast technique for noninvasive fetal ECG extraction. IEEE Trans Biomed Eng 58(2):227ā230
Martinek R, Kelnar M, Koudelka P, Vanus J, BilĆk P, Janku P, Nazeran H, Zidek J (2015) Enhanced processing and analysis of multi-channel noninvasive abdominal foetal ECG signals during labor and delivery. Electron Lett 51(22):1744ā1746
MartĆnez JP, Almeida R, Olmos S, Rocha AP, Laguna P (2004) A wavelet-based ECG delineator: evaluation on standard databases. IEEE Trans Biomed Eng 51(4):570ā581
Massagram W, Boric-Lubecke O, Macchiarulo L, Chen M (2005) Heartrate variability monitoring and assessment system on chip. In: 27th Annual international conference of the engineering in medicine and biology society, 2005. IEEE-EMBS 2005. IEEE, pp 7369ā7372
Massagram W, Hafner N, Chen M, Macchiarulo L, Lubecke VM, Boric-Lubecke O (2010) Digital heart-rate variability parameter monitoring and assessment ASIC. IEEE Trans Biomed Circuits Syst 4(1):19ā26
Meyer C, Gavela JF, Harris M (2006) Combining algorithms in automatic detection of QRS complexes in ECG signals. IEEE Trans Inf Technol Biomed 10(3):468ā475
Milchevski A, Gusev M (2017) Improved pipelined wavelet implementation for filtering ECG signals. Pattern Recogn Lett 95:85ā90
Min YJ, Kim HK, Kang YR, Kim GS, Park J, Kim SW (2013) Design of wavelet-based ECG detector for implantable cardiac pacemakers. IEEE Trans Biomed Circuits Syst 7(4):426ā436
Mishra A, Thakkar F, Modi C, Kher R (2012) ECG signal compression using compressive sensing and wavelet transform. In: 2012 annual international conference of the IEEE engineering in medicine and biology society (EMBC). IEEE, pp 3404ā3407
Moody GB, Mark RG (1990) The MIT-BIH arrhythmia database on CD-ROM and software for use with it. In: Proceedings computers in cardiology. IEEE, pp 185ā188
Moody GB, Mark RG (1996) A database to support development and evaluation of intelligent intensive care monitoring. In: Computers in cardiology. IEEE, pp 657ā660
Nayak C, Saha SK, Kar R, Mandal D (2018) An efficient QRS complex detection using optimally designed digital differentiator. Circuits Syst Signal Process 1ā34
Pan J, Tompkins WJ (1985) A real-time QRS detection algorithm. IEEE Trans Biomed Eng 32(3):230ā236
Pan T, Zhang L, Zhou S (2010). Detection of ECG characteristic points using biorthogonal spline wavelet. In: 2010 3rd International conference on biomedical engineering and informatics (BMEI), vol 2. IEEE, pp 858ā863
Paracha MA, Mohammad SN, Macfarlane PW, Jenkins JM (2003) Implementation of web database for ECG. In: Computers in cardiology. IEEE, pp 271ā274
Pasolli E, Melgani F (2015) Genetic algorithm-based method for mitigating label noise issue in ECG signal classification. Biomed Signal Process Control 19:130ā136
Phyu MW, Zheng Y, Zhao B, Xin L, Wang YS (2009). A real-time ECG QRS detection ASIC based on wavelet multiscale analysis. In: IEEE Asian solid-state circuits conference, 2009. A-SSCC 2009. IEEE, pp 293ā296
PÅawiak P (2018) Novel genetic ensembles of classifiers applied to myocardium dysfunction recognition based on ECG signals. Swarm Evol Comput 39:192ā208
Polania LF, Carrillo RE, Blanco-Velasco M, Barner KE (2011) Compressed sensing-based method for ECG compression. In: 2011 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 761ā764
Polania LF, Carrillo RE, Blanco-Velasco M, Barner KE (2015) Exploiting prior knowledge in compressed sensing wireless ECG systems. IEEE J Biomed Health Inform 19(2):508ā519
Poli R, Cagnoni S, Valli G (1995) Genetic design of optimum linear and nonlinear QRS detectors. IEEE Trans Biomed Eng 42(11):1137ā1141
Qin Q, Li J, Yue Y, Liu C (2017) An adaptive and time-efficient ECG R-peak detection algorithm. J Healthcare Eng
Raj S, Ray KC (2017) ECG signal analysis using DCT-based DOST and PSO optimized SVM. IEEE Trans Instrum Meas 66(3):470ā478
Rakshit M, Das S (2017) An efficient wavelet-based automated R-peaks detection method using Hilbert transform. Biocybern Biomed Eng 37(3):566ā577
Ravanshad N, Rezaee-Dehsorkh H, Lotfi R, Lian Y (2014) A level-crossing based QRS-detection algorithm for wearable ECG sensors. IEEE J Biomed Health Inform 18(1):183ā192
Rhyne VT (1969) A digital system for enhancing the fetal electrocardiogram. IEEE Trans Biomed Eng 1:80ā86
Rodrigues JN, Olsson T, Sornmo L, Owall V (2005) Digital implementation of a wavelet-based event detector for cardiac pacemakers. IEEE Trans Circuits Syst I Regul Pap 52(12):2686ā2698
Sadler BM, Pham T, Sadler LC (1998) Optimal and wavelet-based shock wave detection and estimation. J Acoust Soc Am 104(2):955ā963
Sahambi JS, Tandon SN, Bhatt RKP (1997). Using wavelet transforms for ECG characterization. An online digital signal processing system. IEEE Eng Med Biol Mag 16(1):77ā83
Sannino G, De Pietro G (2018) A deep learning approach for ECG-based heartbeat classification for arrhythmia detection. Futur Gener Comput Syst 86:446ā455
Satija U, Ramkumar B, Manikandan MS (2018) Automated ECG noise detection and classification system for unsupervised healthcare monitoring. IEEE J Biomed Health Inform 22(3):722ā732
Sharma LD, Sunkaria RK (2018) Inferior myocardial infarction detection using stationary wavelet transform and machine learning approach. SIViP 12(2):199ā206
Sharma LN, Tripathy RK, Dandapat S (2015) Multiscale energy and eigenspace approach to detection and localization of myocardial infarction. IEEE Trans Biomed Eng 62(7):1827ā1837
Sharma M, Agarwal S, Acharya UR (2018) Application of an optimal class of antisymmetric wavelet filter banks for obstructive sleep apnea diagnosis using ECG signals. Comput Biol Med 100:100ā113
Shyu LY, Wu YH, Hu W (2004) Using wavelet transform and fuzzy neural network for VPC detection from the Holter ECG. IEEE Trans Biomed Eng 51(7):1269ā1273
Strintzis M, Stalidis G, Magnisalis X, Maglaveras N (1992) Use of neural networks for electrocardiogram (ECG) feature extraction recognition and classification. Neural Netw World 3(4):313ā328
Suarez KV, Silva JC, Berthoumieu Y, Gomis P, Najim M (2007) ECG beat detection using a geometrical matching approach. IEEE Trans Biomed Eng 54(4):641ā650
Sutha P, Jayanthi VE (2018) Fetal electrocardiogram extraction and analysis using adaptive noise cancellation and wavelet transformation techniques. J Med Syst 42(1):21
Sweldens W (1998) The lifting Technique: A construction of second generation wavelets. SIAM J Math Anal 29(2):511ā546
Taddei A, Distante G, Emdin M, Pisani P, Moody GB, Zeelenberg C, Marchesi C (1992) The European ST-T database: standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography. Eur Heart J 13(9):1164ā1172
Tang X, Hu Q, Tang W (2018) A Real-Time QRS Detection System With PR/RT Interval and ST Segment Measurements for Wearable ECG Sensors Using Parallel Delta Modulators. IEEE Transactions on Biomedical Circuits and Systems, (99), pp.1ā11
Thakor NV, Webster JG, Tompkins WJ (1983) Optimal QRS detector. Med Biol Eng Comput 21(3):343ā350
Thungtong A (2017) A robust algorithm for R peak detection based on optimal discrete wavelet transform. In: 2017 14th international joint conference on computer science and software engineering (JCSSE). IEEE, pp 1ā6
Tripathy RK, Dandapat S (2017) Automated detection of heart ailments from 12-lead ECG using complex wavelet sub-band bi-spectrum features. Healthcare Technol Lett 4(2):57
Tsai TH, Kuo WT (2018) An efficient ECG lossless compression system for embedded platforms with telemedicine applications. IEEE Access 6:42207ā42215
Tsai TH, Hong JH, Wang LH, Lee SY (2012) Low-power analog integrated circuits for wireless ECG acquisition systems. IEEE Trans Inf Technol Biomed 16(5):907ā917
Tzabazis A, Eisenried A, Yeomans DC, Hyatt MI (2018) Wavelet analysis of heartrate variability: impact of wavelet selection. Biomed Signal Process Control 40:220ā225
Uthayakumar J, Vengattaraman T, Dhavachelvan P (2018) A survey on data compression techniques: From the perspective of data quality, coding Techniques, data type and applications. J King Saud Univ-Comput Inf Sci
Vafaie MH, Ataei M, Koofigar HR (2014) Heart diseases prediction based on ECG signalsā classification using a genetic-fuzzy system and dynamical model of ECG signals. Biomed Signal Process Control 14:291ā296
Van Bemmel JH, Willems JL (1990) Standardization and validation of medical decision-support systems: the CSE project. Methods Inf Med 29(04):261ā262
Vetterli M, Herley C (1992) Wavelets and filter banks: theory and design. IEEE Trans Signal Process 40(Article)
Vullings R, De Vries B, Bergmans JW (2011) An adaptive Kalman filter for ECG signal enhancement. IEEE Trans Biomed Eng 58(4):1094ā1103
Vuorela T, SeppƤ VP, Vanhala J, Hyttinen J (2010) Design and implementation of a portable long-term physiological signal recorder. IEEE Trans Inf Technol Biomed 14(3):718ā725
Wang HW, Lai YL, Hou MC, Lin SH, Yen BS, Huang YC, Chou LC, Hsu SY, Huang SC, Jan MY (2010) A Ā±6Ā ms- accuracy, 0.68 mm2 and 2.21 Ī¼W QRS detection ASIC. In: Circuits systems symposium, Paris, France. IEEE, pp 1372ā1375
Wang X, Chen M, Macchiarulo L, Boric-Lubecke O (2006) Fully-integrated heartrate variability monitoring system with an efficient memory. In: 28th Annual international conference of the IEEE engineering in medicine and biology society, 2006. EMBSā06. IEEE, pp 5064ā5067
Wang Y, Deepu CJ, Lian Y (2011) A computationally efficient QRS detection algorithm for wearable ECG sensors. In: 2011 Annual international conference of the IEEE engineering in medicine and biology society. IEEE, pp 5641ā5644
Yan L, Bae J, Lee S, Roh T, Song K, Yoo HJ (2011) A 3.9 mW 25-electrode reconfigured sensor for wearable cardiac monitoring system. IEEE J Solid-State Circuits 46(1): 353ā364
Yang G, Xie L, MƤntysalo M, Chen J, Tenhunen H, Zheng LR (2012) Bio-patch design and implementation based on a low-power system-on-chip and paper-based inkjet printing technology. IEEE Trans Inf Technol Biomed 16(6):1043ā1050
YĆ¼celbaÅ Å, YĆ¼celbaÅ C, Tezel G, ĆzÅen S, Yosunkaya Å (2018) Automatic sleep staging based on SVD, VMD, HHT and morphological features of single-lead ECG signal. Expert Syst Appl 102:193ā206
Zhai X, Tin C (2018) Automated ECG classification using dual heartbeat coupling based on convolutional neural network. IEEE Access
Zheng X, Li Z, Shen L, Ji Z (2008) Detection of QRS complexes based on biorthogonal spline wavelet. In: International symposium on information science and engineering, 2008. ISISEā08, vol 2. IEEE, pp 502ā506
Zhou S, Zhang Z, Gu J (2011) Time-domain ECG signal analysis based on smart-phone. In Annual international conference of the IEEE engineering in medicine and biology society, EMBC, 2011. IEEE, pp 2582ā2585
Zidelmal Z, Amirou A, Adnane M, Belouchrani A (2012) QRS detection based on wavelet coefficients. Comput Methods Programs Biomed 107(3):490ā496
Zou Y, Han J, Weng X, Zeng X (2013) An ultra-low power QRS complex detection algorithm based on down-sampling wavelet transform. IEEE Signal Process Lett 20(5):515ā518
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Kumar, A., Kumar, M., Komaragiri, R.S. (2023). Existing Methods to Evaluate Pacemaker Device Performance. In: High Performance and Power Efficient Electrocardiogram Detectors. Energy Systems in Electrical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-5303-3_2
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