Development of a multi-core fiber-Bragg-grating-based axial tip force sensor for left-atrial appendage closure procedure

The left atrial appendage occlusion (LAAO) procedure is a minimally invasive approach to reduce stroke risk in atrial fibrillation (AF) patients who cannot tolerate long-term anticoagulation therapy. Precise occluder deployment is critical to ensure proper sealing of the left atrial appendage (LAA) and avoid complications. This study introduces a compact axial tip force sensor based on multi-core Fiber Bragg Grating (FBG) technology, designed to fit within the 1.25 mm delivery catheter of the Amplatzer Amulet LAA Occluder. The sensor utilizes a Nitinol flexure and a multi-core FBG fiber to measure axial forces while supporting 3D shape sensing. An off -center calibration method compensates for fabrication misalignments, enabling the decoupling of axial and lateral forces. Experimental validation demonstrates the sensor’s ability to accurately measure compressive and tensile forces up to 5 N. The sensor achieved a mean error of 0.16N (1.50% of the full range) and a resolution of 25 mN. The design reduces reliance on the physician’s subjective tactile feedback during deployment, potentially improving precision, minimizing procedural risks, and enhancing patient safety. While the study focuses on axial force sensing, the sensor also supports 3D shape sensing as well as triaxial tip force estimation.

Authors

Institutions

Publication Details

Published
2025-05-22
DOI
https://doi.org/10.1117/12.3062896
Primary Topic
Atrial Fibrillation Management and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of a multi-core fiber-Bragg-grating-based axial tip force sensor for left-atrial appendage closure procedure

J. Van Roosbroeck, Xuan Thao Ha, Johan Vlekken, Mouloud Ourak et al.
Atrial Fibrillation Management and Outcomes
article

Development of a multi-core fiber-Bragg-grating-based axial tip force sensor for left-atrial appendage closure procedure

J. Van Roosbroeck, Xuan Thao Ha, Johan Vlekken, Mouloud Ourak, Emmanuel Vander Poorten
article en

Abstract

The left atrial appendage occlusion (LAAO) procedure is a minimally invasive approach to reduce stroke risk in atrial fibrillation (AF) patients who cannot tolerate long-term anticoagulation therapy. Precise occluder deployment is critical to ensure proper sealing of the left atrial appendage (LAA) and avoid complications. This study introduces a compact axial tip force sensor based on multi-core Fiber Bragg Grating (FBG) technology, designed to fit within the 1.25 mm delivery catheter of the Amplatzer Amulet LAA Occluder. The sensor utilizes a Nitinol flexure and a multi-core FBG fiber to measure axial forces while supporting 3D shape sensing. An off -center calibration method compensates for fabrication misalignments, enabling the decoupling of axial and lateral forces. Experimental validation demonstrates the sensor’s ability to accurately measure compressive and tensile forces up to 5 N. The sensor achieved a mean error of 0.16N (1.50% of the full range) and a resolution of 25 mN. The design reduces reliance on the physician’s subjective tactile feedback during deployment, potentially improving precision, minimizing procedural risks, and enhancing patient safety. While the study focuses on axial force sensing, the sensor also supports 3D shape sensing as well as triaxial tip force estimation.

VIB-KU Leuven Center for Microbiology (BE), D2S International (Belgium) (BE)
Openalex Percentile: Top 80%
Atrial Fibrillation Management and Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.