Learning to Perform Low-Contact Autonomous Nasotracheal Intubation by Recurrent Action-Confidence Chunking with Transformer

TL;DR

This paper introduces an autonomous nasotracheal intubation system using a novel transformer-based model that reduces insertion force and enhances safety, addressing challenges in clinical airway management.

Contribution

The paper presents a new autonomous NTI system with a force-sensing prosthesis and a RACCT transformer model for improved safety and efficiency over existing methods.

Findings

66% reduction in peak insertion force compared to manual methods

Outperforms ACT model in all evaluated aspects

Maintains success rates comparable to manual procedures

Abstract

Nasotracheal intubation (NTI) is critical for establishing artificial airways in clinical anesthesia and critical care. Current manual methods face significant challenges, including cross-infection, especially during respiratory infection care, and insufficient control of endoluminal contact forces, increasing the risk of mucosal injuries. While existing studies have focused on automated endoscopic insertion, the automation of NTI remains unexplored despite its unique challenges: Nasotracheal tubes exhibit greater diameter and rigidity than standard endoscopes, substantially increasing insertion complexity and patient risks. We propose a novel autonomous NTI system with two key components to address these challenges. First, an autonomous NTI system is developed, incorporating a prosthesis embedded with force sensors, allowing for safety assessment and data filtering. Then, the Recurrent Action-Confidence Chunking with Transformer (RACCT) model is developed to handle complex tube-tissue interactions and partial visual observations. Experimental results demonstrate that the RACCT model outperforms the ACT model in all aspects and achieves a 66% reduction in average peak insertion force compared to manual operations while maintaining equivalent success rates. This validates the system's potential for reducing infection risks and improving procedural safety.