An Improved Method for the Estimation and Visualization of Velocity Fields from Gastric High-Resolution Electrical Mapping
High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qua...
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| Published in | IEEE transactions on biomedical engineering Vol. 59; no. 3; pp. 882 - 889 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
IEEE
01.03.2012
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0018-9294 1558-2531 1558-2531 |
| DOI | 10.1109/TBME.2011.2181845 |
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| Abstract | High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0 ° and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7 ° . With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented. |
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| AbstractList | High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0 [compfn] and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7 [compfn] . With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented. High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0 ° and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7 ° . With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented. High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0° and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7°. With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented. High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were i) Simple finite difference ii) Smoothed finite difference and a iii) Polynomial based method. With synthetic data, the accuracy of the simple finite difference method resulted in velocity errors almost twice that of the smoothed finite difference and the polynomial based method, in the presence of activation time error up to 0.5s. With three synthetic cases under various noise types and levels, the smoothed finite difference resulted in average speed error of 3.2% and an average angle error of 2.0° and the polynomial based method had an average speed error of 3.3% and an average angle error of 1.7°. With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the smoothed finite difference method had a lower standard deviation in its velocity estimate than the simple finite difference and the polynomial based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented. High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0° and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7°. With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented.High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0° and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7°. With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented. High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0[Formula Omitted] and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7 [Formula Omitted]. With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented. |
| Author | Paskaranandavadivel, Niranchan Du, Peng OrGrady, Gregory Pullan, Andrew J. Cheng, Leo K. |
| Author_xml | – sequence: 1 givenname: Niranchan surname: Paskaranandavadivel fullname: Paskaranandavadivel, Niranchan email: npas004@aucklanduni.ac.nz organization: Auckland Bioengineering Institute , The University of Auckland, Auckland, New Zealand – sequence: 2 givenname: Gregory surname: OrGrady fullname: OrGrady, Gregory email: gog@ps.gen.nz organization: Department of Surgery and Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand – sequence: 3 givenname: Peng surname: Du fullname: Du, Peng email: peng.du@auckland.ac.nz organization: Auckland Bioengineering Institute , The University of Auckland, Auckland, New Zealand – sequence: 4 givenname: Andrew J. surname: Pullan fullname: Pullan, Andrew J. email: a.pullan@auckland.ac.nz organization: Department of Engineering Science and Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand – sequence: 5 givenname: Leo K. surname: Cheng fullname: Cheng, Leo K. email: l.cheng@auckland.ac.nz organization: Auckland Bioengineering Institute , The University of Auckland, Auckland, New Zealand |
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| Cites_doi | 10.1139/y05-084 10.1152/ajpgi.90380.2008 10.1109/IEMBS.2010.5626616 10.1007/s10439-009-9654-9 10.1007/s10439-009-9870-3 10.1109/10.668746 10.1007/BF02087897 10.1007/s10439-010-0170-8 10.1111/j.1365-2982.2011.01756.x 10.1161/CIRCEP.111.962662 10.1016/j.hrthm.2009.02.023 10.1109/IEMBS.2011.6090497 10.1053/j.gastro.2008.07.020 10.1152/ajpgi.00389.2009 10.1111/j.1365-2982.2011.01739.x 10.1109/TBME.2004.839636 10.1152/ajpgi.00125.2010 10.1109/TBME.2004.826670 10.1111/j.1572-0241.1999.01007.x 10.1111/j.1365-2982.2010.01538.x 10.1114/1.1543936 |
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| Keywords | Cartography Stomach Visualization slow waves High resolution Dysrhythmia Motion estimation Digestive system Speed measurement Travelling wave tube multielec Mapping Velocity distribution finite difference (FD) polynomial fitting ode Polynomial interpolation Signal processing Slow wave structure Biomedical engineering Finite difference method |
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| References | ref12 ref15 ref14 ref11 ref2 ref1 ref17 ref16 du (ref10) 2011 ref18 du (ref21) 2009 ref24 ref23 ref26 gaudette (ref13) 1997 ref25 isaak (ref20) 1989 ref22 (ref19) 0 ref8 ref7 ref9 ref4 ref3 ref6 ref5 9581054 - IEEE Trans Biomed Eng. 1998 May;45(5):563-71 19329365 - Heart Rhythm. 2009 May;6(5):587-91 19224368 - Ann Biomed Eng. 2009 Apr;37(4):839-46 21096180 - Conf Proc IEEE Eng Med Biol Soc. 2010;2010:2608-11 16391712 - Can J Physiol Pharmacol. 2005 Nov;83(11):1031-43 18713627 - Gastroenterology. 2008 Nov;135(5):1601-11 19926815 - Am J Physiol Gastrointest Liver Physiol. 2010 Feb;298(2):G314-21 20618830 - Neurogastroenterol Motil. 2010 Oct;22(10):e292-300 18988693 - Am J Physiol Gastrointest Liver Physiol. 2009 Jan;296(1):G1-8 10201477 - Am J Gastroenterol. 1999 Apr;94(4):1023-8 15651561 - IEEE Trans Biomed Eng. 2005 Jan;52(1):19-29 12680723 - Ann Biomed Eng. 2003 Mar;31(3):250-61 19964973 - Conf Proc IEEE Eng Med Biol Soc. 2009;2009:2527-30 20595620 - Am J Physiol Gastrointest Liver Physiol. 2010 Sep;299(3):G585-92 22255315 - Conf Proc IEEE Eng Med Biol Soc. 2011;2011:4402-5 8769276 - Dig Dis Sci. 1996 Aug;41(8):1538-45 21505175 - Circ Arrhythm Electrophysiol. 2011 Apr;4(2):125-7 22254662 - Conf Proc IEEE Eng Med Biol Soc. 2011;2011:1737-40 21714831 - Neurogastroenterol Motil. 2011 Sep;23(9):e345-55 21838727 - Neurogastroenterol Motil. 2011 Sep;23(9):815-8 15132512 - IEEE Trans Biomed Eng. 2004 May;51(5):847-55 20024624 - Ann Biomed Eng. 2010 Apr;38(4):1511-29 20927594 - Ann Biomed Eng. 2011 Jan;39(1):469-83 |
| References_xml | – ident: ref18 doi: 10.1139/y05-084 – ident: ref1 doi: 10.1152/ajpgi.90380.2008 – ident: ref23 doi: 10.1109/IEMBS.2010.5626616 – ident: ref7 doi: 10.1007/s10439-009-9654-9 – ident: ref15 doi: 10.1007/s10439-009-9870-3 – ident: ref11 doi: 10.1109/10.668746 – ident: ref3 doi: 10.1007/BF02087897 – ident: ref14 doi: 10.1007/s10439-010-0170-8 – start-page: 4402 year: 2011 ident: ref10 article-title: Quantification of velocity anisotropy during gastric electrical arrhythmia publication-title: Conf Proc IEEE Eng Med Biol Soc – ident: ref5 doi: 10.1111/j.1365-2982.2011.01756.x – ident: ref26 doi: 10.1161/CIRCEP.111.962662 – ident: ref25 doi: 10.1016/j.hrthm.2009.02.023 – ident: ref17 doi: 10.1109/IEMBS.2011.6090497 – start-page: 2527 year: 2009 ident: ref21 article-title: Automated detection of gastric slow wave events and estimation of propagation velocity vector fields from serosal high-resolution mapping publication-title: Proc Conf Proc IEEE Eng Med Biol Soc – ident: ref8 doi: 10.1053/j.gastro.2008.07.020 – ident: ref6 doi: 10.1152/ajpgi.00389.2009 – ident: ref9 doi: 10.1111/j.1365-2982.2011.01739.x – year: 0 ident: ref19 – ident: ref24 doi: 10.1109/TBME.2004.839636 – ident: ref2 doi: 10.1152/ajpgi.00125.2010 – ident: ref22 doi: 10.1109/TBME.2004.826670 – ident: ref4 doi: 10.1111/j.1572-0241.1999.01007.x – ident: ref16 doi: 10.1111/j.1365-2982.2010.01538.x – start-page: 339 year: 1997 ident: ref13 publication-title: Computers in Cardiology – year: 1989 ident: ref20 publication-title: An Introduction to Applied Geostatistics – ident: ref12 doi: 10.1114/1.1543936 – reference: 21505175 - Circ Arrhythm Electrophysiol. 2011 Apr;4(2):125-7 – reference: 22255315 - Conf Proc IEEE Eng Med Biol Soc. 2011;2011:4402-5 – reference: 16391712 - Can J Physiol Pharmacol. 2005 Nov;83(11):1031-43 – reference: 21096180 - Conf Proc IEEE Eng Med Biol Soc. 2010;2010:2608-11 – reference: 20927594 - Ann Biomed Eng. 2011 Jan;39(1):469-83 – reference: 21838727 - Neurogastroenterol Motil. 2011 Sep;23(9):815-8 – reference: 19926815 - Am J Physiol Gastrointest Liver Physiol. 2010 Feb;298(2):G314-21 – reference: 9581054 - IEEE Trans Biomed Eng. 1998 May;45(5):563-71 – reference: 22254662 - Conf Proc IEEE Eng Med Biol Soc. 2011;2011:1737-40 – reference: 10201477 - Am J Gastroenterol. 1999 Apr;94(4):1023-8 – reference: 8769276 - Dig Dis Sci. 1996 Aug;41(8):1538-45 – reference: 15132512 - IEEE Trans Biomed Eng. 2004 May;51(5):847-55 – reference: 19964973 - Conf Proc IEEE Eng Med Biol Soc. 2009;2009:2527-30 – reference: 18713627 - Gastroenterology. 2008 Nov;135(5):1601-11 – reference: 20024624 - Ann Biomed Eng. 2010 Apr;38(4):1511-29 – reference: 18988693 - Am J Physiol Gastrointest Liver Physiol. 2009 Jan;296(1):G1-8 – reference: 19224368 - Ann Biomed Eng. 2009 Apr;37(4):839-46 – reference: 20595620 - Am J Physiol Gastrointest Liver Physiol. 2010 Sep;299(3):G585-92 – reference: 12680723 - Ann Biomed Eng. 2003 Mar;31(3):250-61 – reference: 19329365 - Heart Rhythm. 2009 May;6(5):587-91 – reference: 20618830 - Neurogastroenterol Motil. 2010 Oct;22(10):e292-300 – reference: 15651561 - IEEE Trans Biomed Eng. 2005 Jan;52(1):19-29 – reference: 21714831 - Neurogastroenterol Motil. 2011 Sep;23(9):e345-55 |
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| Snippet | High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing... High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing... |
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| SubjectTerms | Algorithms Animals Applied sciences Arrays Detection, estimation, filtering, equalization, prediction Dysrhythmia Electrodes Electrophysiological Phenomena Estimation Exact sciences and technology finite difference (FD) Image processing Information, signal and communications theory multielectrode Muscle Contraction - physiology Muscle, Smooth - physiology Noise polynomial fitting Polynomials Propagation Reliability Reproducibility of Results Signal and communications theory Signal processing Signal Processing, Computer-Assisted Signal, noise slow waves Stomach - physiology Swine Telecommunications and information theory Wave propagation |
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| Title | An Improved Method for the Estimation and Visualization of Velocity Fields from Gastric High-Resolution Electrical Mapping |
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