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Physics-driven Sonification for Improving Multisensory Needle Guidance in Percutaneous Epicardial Access

Human-Computer Interaction 2026-05-27 v1

Abstract

Percutaneous epicardial access (PEA), performed on a beating heart under fluoroscopy, enables arrhythmia treatment. However, advancing a needle toward the thin and moving pericardium remains highly challenging and risky. To address this problem, we present a physics-driven sonification method for Extended Reality (XR)-based multisensory navigation to enhance user perception during the critical needle landing phase in PEA. Dynamic cardiac anatomy from 4D CTA was reconstructed and registered to a real-world coordinate system. Real-time needle tracking provided the position of the needle tip relative to moving cardiac structures and drove an audio-visual feedback module. The visual display presented navigational cues and dynamic anatomy, while the auditory display encoded physiological cardiac states using a multilayer physical membrane model. A phantom study was conducted with twelve cardiologists performing needle insertions under visual-only and multisensory feedback. The multisensory method significantly improved navigation safety (χ2=11.30\chi^2 = 11.30, p<0.01p < 0.01), reducing myocardial contact (3.64% vs. 7.27%) and increasing correct access (90.91% vs. 52.73%). Needle placement accuracy improved, with closer membrane proximity (Cliff delta = 0.19) and reduced variability (p<0.05p < 0.05). Execution time was comparable, while time-accuracy correlations differed significantly between modalities (p<0.01p < 0.01). NASA-TLX indicated lower cognitive load with multisensory guidance (p<0.01p < 0.01). These results demonstrate the feasibility of physics-driven sonification for improving spatiotemporal awareness and supporting user-centered surgical navigation.

Keywords

Cite

@article{arxiv.2604.06911,
  title  = {Physics-driven Sonification for Improving Multisensory Needle Guidance in Percutaneous Epicardial Access},
  author = {Veronica Ruozzi and Sasan Matinfar and Pasquale Vergara and Alessandro Albanesi and Serena Dell'Aversana and Stefano Carugo and Gianluigi Buccoliero and Nassir Navab and Alberto Redaelli and Emiliano Votta},
  journal= {arXiv preprint arXiv:2604.06911},
  year   = {2026}
}

Comments

This work has been submitted to the IEEE for possible publication

R2 v1 2026-07-01T11:59:01.258Z