The sound of surgery-development of an acoustic trocar system enabling laparoscopic sound analysis

Daniel Ostler-Mildner, Luca Wegener, Jonas Fuchtmann, Hubertus Feussner, Dirk Wilhelm, Nassir Navab

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Acoustic information can contain viable information in medicine and specifically in surgery. While laparoscopy depends mainly on visual information, our goal is to develop the means to capture and process acoustic information during laparoscopic surgery. Methods: To achieve this, we iteratively developed three prototypes that will overcome the abdominal wall as a sound barrier and can be used with standard trocars. We evaluated them in terms of clinical applicability and sound transmission quality. Furthermore, the applicability of each prototype for sound classification based on machine learning was evaluated. Results: Our developed prototypes for recording airborne sound from the intraperitoneal cavity represent a promising solution suitable for real-world clinical usage All three prototypes fulfill our set requirements in terms of clinical applicability (i.e., air-tightness, invasiveness, sterility) and show promising results regarding their acoustic characteristics and the associated results on ML-based sound classification. Conclusion: In summary, our prototypes for capturing acoustic information during laparoscopic surgeries integrate seamlessly with existing procedures and have the potential to augment the surgeon’s perception. This advancement could change how surgeons interact with and understand the surgical field.

Keywords

  • Acoustic emission
  • Audio analysis
  • Machine learning
  • Minimally invasive surgery

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