Noninvasive estimation of global activation sequence using the extended Kalman filter

Chenguang Liu; Bin He

doi:10.1109/TBME.2010.2066564

Noninvasive estimation of global activation sequence using the extended Kalman filter

Chenguang Liu, Bin He

Biomedical Engineering

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

Abstract

A new algorithm for 3-D imaging of the activation sequence from noninvasive body surface potentials is proposed. After formulating the nonlinear relationship between the 3-D activation sequence and the body surface recordings during activation, the extended Kalman filter (EKF) is utilized to estimate the activation sequence in a recursive way. The state vector containing the activation sequence is optimized during iteration by updating the error variance/covariance matrix. A new regularization scheme is incorporated into the "predict" procedure of EKF to tackle the ill-posedness of the inverse problem. The EKF-based algorithm shows good performance in simulation under single-site pacing. Between the estimated activation sequences and true values, the average correlation coefficient (CC) is 0.95, and the relative error (RE) is 0.13. The average localization error (LE) when localizing the pacing site is 3.0 mm. Good results are also obtained under dual-site pacing (CC = 0.93, RE = 0.16, and LE = 4.3 mm). Furthermore, the algorithm shows robustness to noise. The present promising results demonstrate that the proposed EKF-based inverse approach can noninvasively estimate the 3-D activation sequence with good accuracy and the new algorithm shows good features due to the application of EKF.

Original language	English (US)
Pages (from-to)	541-549
Number of pages	9
Journal	IEEE Transactions on Biomedical Engineering
Volume	58
Issue number	3 PART 1
DOIs	https://doi.org/10.1109/TBME.2010.2066564
State	Published - Mar 2011

Bibliographical note

Funding Information:
Manuscript received December 12, 2009; revised April 2, 2010, and July 21, 2010; accepted July 24, 2010. Date of publication August 16, 2010; date of current version February 18, 2011. This work was supported in part by the National Institute of Health under Grant RO1HL080093 and National Science Foundation under Grant CBET-0756331. The work of C. Liu was supported in part by a Doctoral Dissertation Fellowship from the Graduate School of the University of Minnesota. Asterisk indicates corresponding author.

Keywords

Extended Kalman filter (EKF)
inverse problem
three-dimensional electrocardiographic imaging

Publisher link

10.1109/TBME.2010.2066564

Find It

Find It at U of M Libraries

Cite this

@article{7a6da949abc841b1a3f20c99b41f4e14,

title = "Noninvasive estimation of global activation sequence using the extended Kalman filter",

abstract = "A new algorithm for 3-D imaging of the activation sequence from noninvasive body surface potentials is proposed. After formulating the nonlinear relationship between the 3-D activation sequence and the body surface recordings during activation, the extended Kalman filter (EKF) is utilized to estimate the activation sequence in a recursive way. The state vector containing the activation sequence is optimized during iteration by updating the error variance/covariance matrix. A new regularization scheme is incorporated into the {"}predict{"} procedure of EKF to tackle the ill-posedness of the inverse problem. The EKF-based algorithm shows good performance in simulation under single-site pacing. Between the estimated activation sequences and true values, the average correlation coefficient (CC) is 0.95, and the relative error (RE) is 0.13. The average localization error (LE) when localizing the pacing site is 3.0 mm. Good results are also obtained under dual-site pacing (CC = 0.93, RE = 0.16, and LE = 4.3 mm). Furthermore, the algorithm shows robustness to noise. The present promising results demonstrate that the proposed EKF-based inverse approach can noninvasively estimate the 3-D activation sequence with good accuracy and the new algorithm shows good features due to the application of EKF.",

keywords = "Extended Kalman filter (EKF), inverse problem, three-dimensional electrocardiographic imaging",

author = "Chenguang Liu and Bin He",

note = "Funding Information: Manuscript received December 12, 2009; revised April 2, 2010, and July 21, 2010; accepted July 24, 2010. Date of publication August 16, 2010; date of current version February 18, 2011. This work was supported in part by the National Institute of Health under Grant RO1HL080093 and National Science Foundation under Grant CBET-0756331. The work of C. Liu was supported in part by a Doctoral Dissertation Fellowship from the Graduate School of the University of Minnesota. Asterisk indicates corresponding author.",

year = "2011",

month = mar,

doi = "10.1109/TBME.2010.2066564",

language = "English (US)",

volume = "58",

pages = "541--549",

journal = "IEEE Transactions on Biomedical Engineering",

issn = "0018-9294",

publisher = "IEEE Computer Society",

number = "3 PART 1",

}

TY - JOUR

T1 - Noninvasive estimation of global activation sequence using the extended Kalman filter

AU - Liu, Chenguang

AU - He, Bin

N1 - Funding Information: Manuscript received December 12, 2009; revised April 2, 2010, and July 21, 2010; accepted July 24, 2010. Date of publication August 16, 2010; date of current version February 18, 2011. This work was supported in part by the National Institute of Health under Grant RO1HL080093 and National Science Foundation under Grant CBET-0756331. The work of C. Liu was supported in part by a Doctoral Dissertation Fellowship from the Graduate School of the University of Minnesota. Asterisk indicates corresponding author.

PY - 2011/3

Y1 - 2011/3

N2 - A new algorithm for 3-D imaging of the activation sequence from noninvasive body surface potentials is proposed. After formulating the nonlinear relationship between the 3-D activation sequence and the body surface recordings during activation, the extended Kalman filter (EKF) is utilized to estimate the activation sequence in a recursive way. The state vector containing the activation sequence is optimized during iteration by updating the error variance/covariance matrix. A new regularization scheme is incorporated into the "predict" procedure of EKF to tackle the ill-posedness of the inverse problem. The EKF-based algorithm shows good performance in simulation under single-site pacing. Between the estimated activation sequences and true values, the average correlation coefficient (CC) is 0.95, and the relative error (RE) is 0.13. The average localization error (LE) when localizing the pacing site is 3.0 mm. Good results are also obtained under dual-site pacing (CC = 0.93, RE = 0.16, and LE = 4.3 mm). Furthermore, the algorithm shows robustness to noise. The present promising results demonstrate that the proposed EKF-based inverse approach can noninvasively estimate the 3-D activation sequence with good accuracy and the new algorithm shows good features due to the application of EKF.

AB - A new algorithm for 3-D imaging of the activation sequence from noninvasive body surface potentials is proposed. After formulating the nonlinear relationship between the 3-D activation sequence and the body surface recordings during activation, the extended Kalman filter (EKF) is utilized to estimate the activation sequence in a recursive way. The state vector containing the activation sequence is optimized during iteration by updating the error variance/covariance matrix. A new regularization scheme is incorporated into the "predict" procedure of EKF to tackle the ill-posedness of the inverse problem. The EKF-based algorithm shows good performance in simulation under single-site pacing. Between the estimated activation sequences and true values, the average correlation coefficient (CC) is 0.95, and the relative error (RE) is 0.13. The average localization error (LE) when localizing the pacing site is 3.0 mm. Good results are also obtained under dual-site pacing (CC = 0.93, RE = 0.16, and LE = 4.3 mm). Furthermore, the algorithm shows robustness to noise. The present promising results demonstrate that the proposed EKF-based inverse approach can noninvasively estimate the 3-D activation sequence with good accuracy and the new algorithm shows good features due to the application of EKF.

KW - Extended Kalman filter (EKF)

KW - inverse problem

KW - three-dimensional electrocardiographic imaging

UR - http://www.scopus.com/inward/record.url?scp=79952171643&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79952171643&partnerID=8YFLogxK

U2 - 10.1109/TBME.2010.2066564

DO - 10.1109/TBME.2010.2066564

M3 - Article

C2 - 20716498

AN - SCOPUS:79952171643

SN - 0018-9294

VL - 58

SP - 541

EP - 549

JO - IEEE Transactions on Biomedical Engineering

JF - IEEE Transactions on Biomedical Engineering

IS - 3 PART 1

ER -

Noninvasive estimation of global activation sequence using the extended Kalman filter

Abstract

Bibliographical note

Keywords

Publisher link

Find It

Other files and links

Fingerprint

Cite this