English

Sonification as a Reliable Alternative to Conventional Visual Surgical Navigation

Sound 2022-07-01 v1 Audio and Speech Processing

Abstract

Despite the undeniable advantages of image-guided surgical assistance systems in terms of accuracy, such systems have not yet fully met surgeons' needs or expectations regarding usability, time efficiency, and their integration into the surgical workflow. On the other hand, perceptual studies have shown that presenting independent but causally correlated information via multimodal feedback involving different sensory modalities can improve task performance. This article investigates an alternative method for computer-assisted surgical navigation, introduces a novel sonification methodology for navigated pedicle screw placement, and discusses advanced solutions based on multisensory feedback. The proposed method comprises a novel sonification solution for alignment tasks in four degrees of freedom based on frequency modulation (FM) synthesis. We compared the resulting accuracy and execution time of the proposed sonification method with visual navigation, which is currently considered the state of the art. We conducted a phantom study in which 17 surgeons executed the pedicle screw placement task in the lumbar spine, guided by either the proposed sonification-based or the traditional visual navigation method. The results demonstrated that the proposed method is as accurate as the state of the art while decreasing the surgeon's need to focus on visual navigation displays instead of the natural focus on surgical tools and targeted anatomy during task execution.

Keywords

Cite

@article{arxiv.2206.15291,
  title  = {Sonification as a Reliable Alternative to Conventional Visual Surgical Navigation},
  author = {Sasan Matinfar and Mehrdad Salehi and Daniel Suter and Matthias Seibold and Navid Navab and Shervin Dehghani and Florian Wanivenhaus and Philipp Fürnstahl and Mazda Farshad and Nassir Navab},
  journal= {arXiv preprint arXiv:2206.15291},
  year   = {2022}
}

Comments

19 pages, 7 figures

R2 v1 2026-06-24T12:09:42.700Z