Laplacian ECG moment of activation detection algorithm during pacing

Besio, Walter G.; Aoki, Kota

doi:10.1109/iembs.2004.1403317

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…This appears to be an inappropriate model in the present study for at least two reasons: (i) the LECG are not always biphasic waveform (doublet) and (ii) the dipoles move along complicated paths. A new approach with high noise immunity was found when the Lead II ECG was used as a reference and correlated with the LECG (Besio et al 2001, Besio 2001, Besio and Kota 2004. The correlation results in leading or lagging times as MOA of the LECG.…”

Section: Discussionmentioning

confidence: 99%

“…In some cases, the automated procedure for calculating MOA (Besio and Kota 2004) chose an incorrect value. The Lead II ECG QRS wave is about 100 ms in healthy subjects.…”

Section: Discussionmentioning

confidence: 99%

“…The time offset between these two similar waves was designated as the MOA with the units in (ms). A new algorithm for detecting MOA (Besio and Kota 2004) was automated and achieved greater than 99% efficiency on simulated signals with noise. The MOA could be zero, which means the LECG wave happens at the same time as the Lead II ECG R-wave peak.…”

Section: Lecg Moa Algorithmmentioning

confidence: 99%

“…The LECG data were baseline-adjusted for drift before it was Weiner filtered (He andWu 1999, He 1998). In postprocessing, each LECG signal was windowed and synchronized relative to the simultaneously recorded Lead II ECG R-wave peak after performing QRS detection (Besio and Kota 2004). A 1600-point window digital Weiner filter was applied to cover one 800 ms cardiac cycle.…”

Section: Lecg Post-processingmentioning

confidence: 99%

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Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping

Besio

Chen

2007

Physiol. Meas.

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The electrocardiogram (ECG) provides useful global temporal assessment of the cardiac activity, but has limited spatial capabilities. The Laplacian electrocardiogram (LECG), an improvement over the ECG, provides high spatiotemporal distributed information about cardiac electrical activation. We designed and developed LECG tripolar concentric ring electrode active sensors based on the finite element algorithm 'nine-point method' (NPM). The active sensors were used in an array of 6 by 12 (72) locations to record bipolar and tripolar LECG from the body surface over the anterolateral chest. Compared to bipolar LECG, tripolar LECG showed significantly higher spatial selectivity which may be helpful in inferring information about cardiac activations detected on the body surface. In this study the moment of activation (MOA), an indicator of a depolarization wave passing below the active sensors, was used to surmise possible timing information of the cardiac electrical activation below the active sensors' recording sites. The MOA on the body surface was used to generate isochronal maps that may some day be used by clinicians in diagnosing arrhythmias and assessing the efficacy of therapies.

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Section: Discussionmentioning

confidence: 99%

“…In some cases, the automated procedure for calculating MOA (Besio and Kota 2004) chose an incorrect value. The Lead II ECG QRS wave is about 100 ms in healthy subjects.…”

Section: Discussionmentioning

confidence: 99%

Section: Lecg Moa Algorithmmentioning

confidence: 99%

Section: Lecg Post-processingmentioning

confidence: 99%

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Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping

Besio

Chen

2007

Physiol. Meas.

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De-noising of Electrocardiogram (ECG) with Adaptive Filter Using MATLAB

Makwana

Gupta

2015

2015 Fifth International Conference on Communication Systems and Network Technologies

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Problem associated with biomedical signal like ECG is to extract noise cause by high frequency interference, electromagnetic fields, power line interference and body movement. It is difficult to apply filters with fixed coefficients to reduce random noises. Adaptive filter technique is required to overcome this problem. This paper presents an innovative technique for estimation of ECG waves using Adaptive Noise Cancellation (ANC) algorithm, widrow-hoff LMS algorithm. Comparisons are made for original signal to noisy. Simulations are done for random noise pattern in matlab.

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Non-invasive Laplacian Electrocardiography and Moment of Activation Mapping

Besio

Chen

2006

2006 International Conference of the IEEE Engineering in Medicine and Biology Society

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Laplacian Electrocardiogram (LECG) is a non-invasive approach providing high spatiotemporal distributed information of cardiac electrical activity. Recently researchers have recorded surface potentials from monopolar disc electrodes to estimate the Laplacian using finite difference algorithms or spline surface Laplacian estimators. Bipolar and quasi-bipolar electrodes have also been used to record LECG directly. Here based on the "Nine Point Method" (NPM), Laplacian tripolar concentric ring electrode active sensors were designed. High spatiotemporal resolution body surface LECG using the new tripolar active sensors was recorded. Moment of activation (MOA) isochronal maps used to detect cardiac electrical activation patterns exhibited on the body surface was also generated.

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Laplacian ECG moment of activation detection algorithm during pacing

Cited by 4 publications

References 7 publications

Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping

Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping

De-noising of Electrocardiogram (ECG) with Adaptive Filter Using MATLAB

Non-invasive Laplacian Electrocardiography and Moment of Activation Mapping

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