ECG electrode localization using 3D visual reconstruction
Body surface potential maps (BSPMs) derived from multi-channel ECG recordings enable the detection and diagnosis of electrophysiological phenomena beyond the standard 12-lead ECG. In this work, we developed two AI-based methods for the automatic detection of location of the electrodes used for BSPM:...
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Frontiers Media S.A.
2025-03-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2025.1504319/full |
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| author | Ayoub El Ghebouli Amaël Mombereau Michel Haïssaguerre Michel Haïssaguerre Rémi Dubois Laura R. Bear |
| author_facet | Ayoub El Ghebouli Amaël Mombereau Michel Haïssaguerre Michel Haïssaguerre Rémi Dubois Laura R. Bear |
| author_sort | Ayoub El Ghebouli |
| collection | DOAJ |
| description | Body surface potential maps (BSPMs) derived from multi-channel ECG recordings enable the detection and diagnosis of electrophysiological phenomena beyond the standard 12-lead ECG. In this work, we developed two AI-based methods for the automatic detection of location of the electrodes used for BSPM: a rapid method using a specialized 3D Depth Sensing (DS) camera and a slower method that can use any 2D camera. Both methods were validated on a phantom model and in 7 healthy volunteers. With the phantom model, both 3D DS camera and 2D camera method achieved an average localization error less than 2 mm when compared to CT-scan or an Electromagnetic Tracking System (ETS). With healthy volunteers, the 3D camera yielded average 3D Euclidean distances ranging from 2.61 ± 1.2 mm to 5.78 ± 3.09 mm depending on the patient, similar to that seen with 2D camera (ranging from 2.45 ± 1.32 mm to 5.88 ± 2.73 mm). These results demonstrate high accuracy and provide practical alternatives to traditional imaging techniques, potentially enhancing the interest of BSPMs in a clinical setting. |
| format | Article |
| id | doaj-art-2da8054d910b4bea8160610a6937ae36 |
| institution | OA Journals |
| issn | 1664-042X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj-art-2da8054d910b4bea8160610a6937ae362025-08-20T02:05:20ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2025-03-011610.3389/fphys.2025.15043191504319ECG electrode localization using 3D visual reconstructionAyoub El Ghebouli0Amaël Mombereau1Michel Haïssaguerre2Michel Haïssaguerre3Rémi Dubois4Laura R. Bear5University Bordeaux, Institut national de la sante et de la recherche medicale (INSERM), U-1045, IHU Liryc, Le Centre de Recherche Cardio-Thoracique de Bordeaux (CRCTB), Bordeaux, FranceUniversity Bordeaux, Institut national de la sante et de la recherche medicale (INSERM), U-1045, IHU Liryc, Le Centre de Recherche Cardio-Thoracique de Bordeaux (CRCTB), Bordeaux, FranceUniversity Bordeaux, Institut national de la sante et de la recherche medicale (INSERM), U-1045, IHU Liryc, Le Centre de Recherche Cardio-Thoracique de Bordeaux (CRCTB), Bordeaux, FranceCHU de Bordeaux, Cardiology-Electrophysiology and Stimulation Department, Institut national de la sante et de la recherche medicale (INSERM), U-1045, Bordeaux, FranceUniversity Bordeaux, Institut national de la sante et de la recherche medicale (INSERM), U-1045, IHU Liryc, Le Centre de Recherche Cardio-Thoracique de Bordeaux (CRCTB), Bordeaux, FranceUniversity Bordeaux, Institut national de la sante et de la recherche medicale (INSERM), U-1045, IHU Liryc, Le Centre de Recherche Cardio-Thoracique de Bordeaux (CRCTB), Bordeaux, FranceBody surface potential maps (BSPMs) derived from multi-channel ECG recordings enable the detection and diagnosis of electrophysiological phenomena beyond the standard 12-lead ECG. In this work, we developed two AI-based methods for the automatic detection of location of the electrodes used for BSPM: a rapid method using a specialized 3D Depth Sensing (DS) camera and a slower method that can use any 2D camera. Both methods were validated on a phantom model and in 7 healthy volunteers. With the phantom model, both 3D DS camera and 2D camera method achieved an average localization error less than 2 mm when compared to CT-scan or an Electromagnetic Tracking System (ETS). With healthy volunteers, the 3D camera yielded average 3D Euclidean distances ranging from 2.61 ± 1.2 mm to 5.78 ± 3.09 mm depending on the patient, similar to that seen with 2D camera (ranging from 2.45 ± 1.32 mm to 5.88 ± 2.73 mm). These results demonstrate high accuracy and provide practical alternatives to traditional imaging techniques, potentially enhancing the interest of BSPMs in a clinical setting.https://www.frontiersin.org/articles/10.3389/fphys.2025.1504319/fullBSPMECG electrodes localization3D camera2D cameraAI |
| spellingShingle | Ayoub El Ghebouli Amaël Mombereau Michel Haïssaguerre Michel Haïssaguerre Rémi Dubois Laura R. Bear ECG electrode localization using 3D visual reconstruction Frontiers in Physiology BSPM ECG electrodes localization 3D camera 2D camera AI |
| title | ECG electrode localization using 3D visual reconstruction |
| title_full | ECG electrode localization using 3D visual reconstruction |
| title_fullStr | ECG electrode localization using 3D visual reconstruction |
| title_full_unstemmed | ECG electrode localization using 3D visual reconstruction |
| title_short | ECG electrode localization using 3D visual reconstruction |
| title_sort | ecg electrode localization using 3d visual reconstruction |
| topic | BSPM ECG electrodes localization 3D camera 2D camera AI |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2025.1504319/full |
| work_keys_str_mv | AT ayoubelghebouli ecgelectrodelocalizationusing3dvisualreconstruction AT amaelmombereau ecgelectrodelocalizationusing3dvisualreconstruction AT michelhaissaguerre ecgelectrodelocalizationusing3dvisualreconstruction AT michelhaissaguerre ecgelectrodelocalizationusing3dvisualreconstruction AT remidubois ecgelectrodelocalizationusing3dvisualreconstruction AT laurarbear ecgelectrodelocalizationusing3dvisualreconstruction |