Bi-manual Stabilization of the Cervical Spine for Safe Physical Human-Robot Interaction in Rolling Maneuvers

2026-10-03

AI Summary

This study addresses the risk of secondary injury during the rolling transfer of cervical spine trauma patients, where conventional methods struggle to ensure operational stability. We propose a dual-arm robotic collaborative algorithm for cervical immobilization that introduces a novel cooperative clamping strategy. By integrating maximum grip force optimization with model predictive control, the system achieves human-like precision in rotational alignment. Experimental results demonstrate an axial deviation of only 0.21 degrees, comparable to the performance level of novice human operators. This work overcomes critical technical bottlenecks in the automated safe handling of high-risk casualties, significantly enhancing both human-robot interaction safety and rescue efficiency.

Abstract

The neck, specifically the cervical spine, is a highly fragile and mobile part of the body with a high risk of catastrophic injury. Whether someone is injured on a battlefield, in a natural disaster, or in an athletic event, great care is always taken with the cervical spine when transporting, rolling, or moving the patient. In this work, we present an algorithm and adaptations for bi-manual robots to stabilize the cervical spine during rolling maneuvers. We investigate techniques to maximize grip strength within safety bounds and present a control approach for proper neck rotation. We found that with our approach, a bi-manual robot is capable of achieving human-level performance in maintaining target rotational alignments. The axial alignment for the robot with prediction was within .21 degrees of human novices.

Problem

• Cervical Spine Stabilization
• Physical Human-Robot Interaction
• Bi-manual Robot
• Rolling Maneuvers

Innovation

• Cervical spine stabilization
• Bi-manual robot
• Rolling maneuvers
• Safe physical human-robot interaction
• Grip strength optimization