A comparison of simulated QRS isointegral maps resulting from pacing at adjacent sites: Implications for the spatial resolution of pace mapping using body surface potentials*1

1998 ◽  
Vol 31 ◽  
pp. 135-144
Author(s):  
R HREN
Keyword(s):  
Spatial Resolution ◽  
Body Surface ◽  
Surface Potentials ◽  
Pace Mapping

Spatial resolution of epicardial pace mapping using body surface potentials

2000 ◽  
Vol 440 (S1) ◽  
pp. R123-R125 ◽  
Author(s):  
Silvia Samarin ◽  
Rok Hren ◽  
Roman Trobec ◽  
Viktor Avbelj ◽  
Borut Geršak
Keyword(s):  
Spatial Resolution ◽  
Body Surface ◽  
Surface Potentials ◽  
Epicardial Pace ◽  
Pace Mapping

scholarly journals Resolution of pace mapping stimulus site separation using body surface potentials.

Circulation ◽  
1994 ◽  
Vol 90 (1) ◽  
pp. 462-468 ◽  
Author(s):  
L S Green ◽  
R L Lux ◽  
P R Ershler ◽  
R A Freedman ◽  
F I Marcus ◽  
...  
Keyword(s):  
Body Surface ◽  
Surface Potentials ◽  
Stimulus Site ◽  
Pace Mapping

scholarly journals Cardiac Activation Maps Reconstruction: A Comparative Study Between Data-Driven and Physics-Based Methods

2021 ◽  
Vol 12 ◽  
Author(s):  
Amel Karoui ◽  
Mostafa Bendahmane ◽  
Nejib Zemzemi
Keyword(s):  
Neural Networks ◽  
Comparative Study ◽  
Body Surface ◽  
Data Driven ◽  
Diagnostic Tools ◽  
L1 Norm ◽  
Surface Potentials ◽  
Body Surface Potential ◽  
Data Driven Approach ◽  
Classic Technique

One of the essential diagnostic tools of cardiac arrhythmia is activation mapping. Noninvasive current mapping procedures include electrocardiographic imaging. It allows reconstructing heart surface potentials from measured body surface potentials. Then, activation maps are generated using the heart surface potentials. Recently, a study suggests to deploy artificial neural networks to estimate activation maps directly from body surface potential measurements. Here we carry out a comparative study between the data-driven approach DirectMap and noninvasive classic technique based on reconstructed heart surface potentials using both Finite element method combined with L1-norm regularization (FEM-L1) and the spatial adaptation of Time-delay neural networks (SATDNN-AT). In this work, we assess the performance of the three approaches using a synthetic single paced-rhythm dataset generated on the atria surface. The results show that data-driven approach DirectMap quantitatively outperforms the two other methods. In fact, we observe an absolute activation time error and a correlation coefficient, respectively, equal to 7.20 ms, 93.2% using DirectMap, 14.60 ms, 76.2% using FEM-L1 and 13.58 ms, 79.6% using SATDNN-AT. In addition, results show that data-driven approaches (DirectMap and SATDNN-AT) are strongly robust against additive gaussian noise compared to FEM-L1.

scholarly journals Contributions of the 12 Segments of Left Ventricular Myocardium to the Body Surface Potentials

2007 ◽  
pp. 300-309
Author(s):  
Juho Väisänen ◽  
Jesús Requena-Carrión ◽  
Felipe Alonso-Atienza ◽  
Jari Hyttinen ◽  
José Luis Rojo-Álvarez ◽  
...  
Keyword(s):  
Body Surface ◽  
Ventricular Myocardium ◽  
Left Ventricular ◽  
The Body ◽  
Left Ventricular Myocardium ◽  
Surface Potentials
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