Abstract

In order to make a benefit from body surface potential mapping; this is need to measure the potential from a multi-electrode system. Spatio-temporal information represents the potential distribution over the body surface. This distribution represents the variation of the potential with respect to amplitude and time simultaneously. In this paper, The cardiac muscle state from body surface potential maps (BSPM) non-invasively is evaluated using chest electrodes for a better cardiac disease diagnosis and for enhancing the diagnostic power as compared to the standard 12-lead ECG system.

References

• Aryl. Gold Berger El Sevier "Clinical Electrocardiograph a simplified approach". Seventh edition.
• Willam F.Ganong "Review of medical physiology" eighteenth edition.
• John R. Hampton" The ECG Mode Easy" Sixth edition.
• Daniel R. Richandson “Cardiopulmonary system" 1st Edition
• Dan H B.Brooks "Electrical imaging of heart ,electrophysiological underpinnings and signal processing opportunities "National Science Foundation May 4 ,1998
• Jiapupan And J. Tompkinsn .A Real Time QRS Detection Algorithm. " IEEE Trans. on Biomedical Eng.,Vol. BME-32, 1985: 230-239
• M.Nygards .A QRS delineation Algorithm with Low Sensitivity To Noise And Morphological Changes. " Comput Cardial. 1981 pp 347-350.
• A. Ligtenberg and M Kunt , " A Robust – Digital QRS – Detection Algorithm For Arrhythmia Monitoring " Comput. Biomedical. Res. Vol .16 pp.273-230, 1981 .
• Hamilton, Patrick S.Tompkins, Willis J." Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database "Biomedical Engineering, IEEE Transactions on  Volume:BME-331986 Page(s):1157 – 1165
• Afonso, V.X. , Tompkins,"ECG Beat detection using filter banks" Biomedical Engineering, IEEE Transactions on  (Volume:46 , Issue: 2 ) 1999, pp.192-202.
• P. S. Hamilton and W. J. Tompkins, “Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database,” IEEE Trans. Biomed. Eng., vol. BME-33, pp. 1157–1165, 1986.
• Hanninen H, Nenonen J, Mäkijärvi M, et al. Perspectives on body surface mapping in acute ischemic syndromes. Intl J Bioelectromagnetism. 2003; 5(1): 4-6.
• Ame Sippensog , Roen Wegen and Andrea Natale. Potential role of body surface ECG mapping for localization of atrial fibrillation trigger sites. Journal of Electrocardiology. 2004; 37: 47-52.
• Carley SD, Jenkins M, Jones KM. Body surface mapping versus the standard 12 lead ECG in the detection of myocardial infarction amongst emergency department patients: A Bayesian approach. Resuscitation. 2005; 64(3): 309-314.
• Hans Koch ,Axel Richter .Composition Of Approximated Body surface Potential maps by Utilizing a Common 12 lead ECG Device: IEEE Transaction on Biomedical Engineering .2005 vol 52 no 3,463-469
• Tragardh E, Engblom H, Pahlm O. How many ECG leads do we need? Cardiol Clin. 2006; 24(3): 317-330.
• Lefebvre C, Hoekstra J. Early detection and diagnosis of acute myocardial infarction: The potential for improved care with next-generation, user-friendly electrocardiographic body surface mapping. Am J Emerg Med. 2007; 25(9): 1063-1072.
• C.G.Xanthis, P.M.Bonovas. Inverse Problem of ECG for Different Equivalent Cardiac Sources. PIERS On Line ,vol 3 , No 8 , 2007: 1222-1227.
• Mohamed Aouf, Sherief Samy and Amr Sharawy “Pseudo Body Surface Potential Mapping on Heart Using 3D Wavelet Transform “International Journal of Computer Applications (0975 – 8887) Volume 80– No.8, 2013.
• Mohamed Aouf ,Mohammed Salem and Amr Sharawy” Using 3D Wavelet Transform For Cardiac Mapping De-noising Of Heart Anterior Surface Ischemia” International Journal of Intelligent Computing and Information Science, 2015 .