Segment classification of ecg data and construction of scatter plots using principal component analysis

Journal of Mechanics in Medicine and Biology

Volumn 8, Issue 3, 2008, Pages 421-458

  Chawla, M P S ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

Author keywords

Diagnostic; Electrocardiogram; Feature extraction; Orientation; Principal component analysis; Scatter plots; Validation; Variance estimator; Wavelet transforms

Indexed keywords

EID: 53249149320     PISSN: 02195194     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219519408002681     Document Type: Article

References (59)

1. Chawla MPS, Verma HK, Kumar V, A new statistical PCA-ICA algorithm for location of R-peaks in ECG, Int J Cardiol 129:146-148, 2008.
2. Chawla MPS, Verma HK, Kumar V, ECG modeling and QRS detection using principal component analysis, in IET Proceedings of the Third International Conference on Medical Signal and Information Processing (MEDSIP-06), Paper no. 04, Glasgow, UK, July 17-19, 2006.
3. Ranjith P, Baby PC, Joseph P, ECG analysis using wavelet transform: Application to myocardial ischemia detection, ITBM-RBM 24 44-47, 2003.
4. Magaveras N, Stamkopoulos T, Pappas C, Strintzis MG, An adaptive backpropagation neural network for real-time ischemia episodes detection: Development and performance analysis using the European ST-T database, IEEE Trans Biomed Eng 45:805-813, 1998.
5. Golden DP Jr, Wolthuis RA, Hoffler GW, A spectral analysis of the normal resting electrocardiogram, IEEE Trans Biomed Eng 20 5):366-372, 1973.
6. Mallat S, Zero crossing of a wavelet transform, IEEE Trans Inf Theory 37(4):1019-1033, 1991.
7. Raghuveer MR, Bopardikar S, Wavelet Transforms: Introduction to Theory and Applications, 2nd ed., Addison Wesley, Boston, MA, 1996.
8. Special issue on wavelets, Proc IEEE 84(4), 1996.
9. Raya MAD, Sison LG, Adaptive noise canceling of motion artifact in stress ECG signals using accelerometer, in Proc 2nd Joint EMBS/BMES Conf, Houston, pp. 1756-1757, 2002.
10. Rompelman O, Ross HH, Coherent averaging technique: A tutorial review, Part 1: Noise reduction and the equivalent filter, J Biomed Eng 8(1):30-35, 1986.
11. Webster JG, Reducing motion artifacts and interference in biopotential recording, IEEE Trans Biomed Eng 31(12):823-826, 1984.
12. Chawla MPS, Verma HK, Kumar V, Modeling and feature extraction of ECG using independent component analysis, in Proc IET APSCOM-06, Paper no. 040, Hong Kong, Oct 30-Nov 2, 2006.
13. Chawla MPS, Parameterization and R-peak error estimations of ECG signals using independent component analysis, Comput Math Methods Med 8 4):263-285, 2007.
14. Raya MAD, Sison LG, Adaptive noise canceling of motion artifact in stress ECG signals using accelerometer, in Proc 2nd Joint EMBS/BMES Conf, Houston, pp. 1756-1757, 2002.
15. Outram NJ, Intelligent pattern analysis of the foetal electrocardiogram, PhD thesis, School of Electronic, Communication and Electrical Engineering, University of Plymouth, UK, 1997.
16. Hamilton PS, Tompkins WJ, Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database, IEEE Trans Biomed Eng 33:115-165, 1986.
17. Standing P, Dent M, Craig A, Glenville B, Changes in referral patterns to cardiac out-patient clinics with ambulatory ECG monitoring in general practice, Br J Cardiol 6:394-398, 2001.
18. Roweis S, Saul L, Nonlinear dimensionality reduction by local linear embedding, Science 290(5500):2323-2326, 2000.
19. Mallat S, Zhong S, Characterization of signals from multiscale edges, IEEE Trans Pattern Anal Mach Intell 14(7):710-732, 1992.
20. Xue Q, Hu YH, Tompkins WJ, Neural-network-based adaptive filtering for QRS detection, IEEE Trans Biomed Eng 39:317-329, 1992.
21. Chawla MPS, Verma HK, Kumar V, Data reduction and removal of base-line wander using principal component analysis, Digit Signal Process (under review).
22. Keselbrener L, Keselbrener M, Akselrod S, Nonlinear high pass filter for R-wave detection in ECG signal, Med Eng Phys 19(5):481-484, 1997.
23. Chawla MPS, PCA and ICA processing methods for removal of artifacts and noise in electrocardiograms: A survey and comparison, Appl Soft Comput (under review).
24. Chawla MPS, Verma HK, Kumar V, A new approach to ECG modeling using principal component analysis, in Proc NCCCB-06, Paper no. BM4, Kota, India, 2006.
25. Ziehe A, Lasko P, Muller KR, Nolte G, A linear least-squares algorithm for joint diagonalization, in Proc Int Conf on Independent Component Analysis and Blind Signal Separation (ICA-03), Nara, Japan, pp. 469-474, 2003.
26. Burbank DP, Webster JG, Reducing skin potential motion artifacts by skin abrasion, Med Biol Eng Comput 16:31-38, 1978.
27. Milanesi M, Martini N, Vanello N, Positano V, Santarelli MF, Paradiso R, De Rossi D, Landini L, Multichannel techniques for motion artifacts removal from electrocardiographic signals, Conf Proc IEEE Eng Med Biol Soc 1:3391-3394, 2006.
28. Opie LH, Heart Physiology, Lippincott Williams & Wilkins, Philadelphia, 2004.
29. Bernat EM, Williams WJ, Gehring WJ, Decomposing ERP time-frequency energy using PCA, Clin Neurophysiol 116:1314-1334, 2005.
30. Kohler BU, Hennig C, Orglmeister R, The principles of software QRS detection, IEEE Eng Med Biol Mag 21:42-57, 2002.
31. Jalaleddine S, Hutchens C, Strattan R, Coberly W, ECG data compression techniques: A uniform approach, IEEE Trans Biomed Eng 37 4):329-343, 1990.
32. Nagasaka Y, Iwata A, Data compression of long time ECG recording using BP and PCA neural networks, IEICE Trans Inf Syst 76-D 12):1434-1442, 1993.
33. Chawla MPS, Verma HK, Kumar V, Artifacts and noise removal in electrocardiograms using independent component analysis, Int J Cardiol, Aug 7, 2007 (Epub ahead of print).
34. Chawla MPS, Parameterization and correction of electrocardiogram signals using independent component analysis, J Mech Med Biol 7 4):355-379, 2007.
35. Chawla MPS, Verma HK, Kumar V, PCA-ICA method for detection of QRS complexes and location of R-peaks in electrocardiograms, Digit Signal Process (under review).
36. Chawla MPS, A comparative analysis of principal component and independent component techniques for electrocardiograms, accepted to Int J Neural Comput Appl.
37. Thakor NV, Sherman D,Wavelet (time-scale) analysis in biomedical signal processing, in Bronzino JD (ed.), Biomedical Engineering Handbook, CRC Press, Boca Raton, FL, pp. 886-906, 1995.
38. Saxena SC, Kumar V, Hamde ST, QRS detection using new wavelets, J Med Eng Technol 26(1):7-15, 2002.
39. Singh D, Kumar V, Chawla MPS, Wavelet filter evaluation for HRV signal processing, in Proc IET MEDSIP'06, Paper no. 037, Glasgow, UK, July, 2006.
40. Saxena SC, Kumar V, Hamde ST, ECG data compression using non-redundant templates, IETE Tech Rev 17(5):299-310, 2000.
41. Kulkarni PK, Kumar V, Verma HK, ECG data compression using fast Walsh transform and its clinical acceptability, Int J Syst Sci 28 8):831-836, 1997.
42. Koutsogiannis GS, Soraghan JJ, Selection of number of principal components for denoising signals, Electron Lett 38:664-666, 2002.
43. Tarvainen MP, Niskanen JP, Karjalainen PA, Laitinen T, Lyyra-Laitinen T, Noise sensitivity of a principal component regression based RT interval variability estimation method, Conf Proc IEEE Eng Med Biol Soc 1:3098-3101, 2006.
44. Thakor N, Sun Y, Rix H, Caminal P, Multi-wave: A wavelet-based ECG data compression algorithm, IEICE Trans Inf Syst E 76-D 12):1462-1469, 1993.
45. Gritzali F, Frangakis G, Papakonstantinou G, Detection of the P and T waves in an ECG, J Comput Biomed Res 22:83-91, 1989.
46. Zhang H, Zhang LQ, ECG analysis based on PCA and support vector machines, in Proc ICNN&B'05, pp. 743-747, 2005.
47. Barros AK, Mansour A, Ohnishi N, Removing artifacts from electrocardiographic signals using independent components analysis, Neurocomputing 22:173-186, 1998.
48. Li C, Zheng C, Tai C, Detection of ECG characteristic points using wavelet transform, IEEE Trans Biomed Eng 42(1):21-28, 1995.
49. Vetterly M, Kovacevic J, Wavelet and Subband Coding, 1st ed., Prentice Hall, Upper Saddle River, NJ, 1995.
50. Chawla MPS, Verma HK, Kumar V, Independent component analysis: A novel technique for removal of artifacts and base-line wander in ECG, in Proc CISCON-06, Manipal Institute of Technology, India, pp. 14-18, 2006.
51. Cardoso JF, Blind signal separation: Statistical principles, Proc IEEE 86(10):2009-2025, 1998.
52. Kaplan ST, Principal and independent component analysis for seismic data, Master's thesis, University of British Columbia, Canada, 2003.
53. Chawla MPS, Detection of indeterminacies in corrected ECG signals using parameterized multidimensional independent component analysis, accepted to Int J Comput Math Methods Med.
54. Friesen GM, Jannett TC, Jadallah MA, Yates SL, Quint SR, Nagle HT, A comparison of the noise sensitivity of nine QRS detection algorithms, IEEE Trans Biomed Eng 37:85-98, 1990.
55. So HH, Chan KL, Development of QRS detection method for real-time ambulatory cardiac monitor, in IEEE Proc 19th Annual International Conference EMBS, pp. 289-292, 1997.
56. Bronzino JD, The Biomedical Engineering Handbook, 2nd ed., CRC Press, Boca Raton, FL, 2000.
57. Trahanias PE, An approach to QRS complex detection using mathematical morphology, IEEE Trans Biomed Eng 40(2):201-205, 1993.
58. Kohler BU, Hennig C, Orglmeister R, The principles of software QRS detection, IEEE Eng Med Biol Mag 21:42-57, 2002.
59. Keselbrener L, Keselbrener M, Akselrod S, Nonlinear high pass filter for R-wave detection in ECG signal, Med Eng Phys 19(5):481-484, 1997.