Human-Robot Teaming Field Deployments: A Comparison Between Verbal and Non-verbal Communication

2025-06-10

AI Summary

This study investigates optimal human–robot communication modalities in emergency resuscitation, specifically examining how auditory and visual cues affect clinicians’ cognitive load, collaborative efficiency, and acceptance. We deployed a Robot-assisted Crash Cart (RCC) in real-world hospital resuscitation settings and conducted a between-subjects controlled experiment, employing NASA-TLX for cognitive load assessment, behavioral coding for performance analysis, and validated attitude questionnaires for user acceptance. Results indicate that auditory feedback significantly reduces mental demand and physical effort, thereby enhancing overall task efficiency and system acceptance; although it slightly increases frustration, the net effect remains positive. This work addresses a critical gap in empirical research on multimodal human–robot interaction under high-stakes clinical conditions. It provides ecologically valid evidence and transferable design principles for interactive intelligent medical devices, grounded in authentic emergency care environments.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Interaction Techniques and Devices
• Cognitive Modeling & Cognitive Systems: Affective Computing

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Healthcare workers (HCWs) encounter challenges in hospitals, such as retrieving medical supplies quickly from crash carts, which could potentially result in medical errors and delays in patient care. Robotic crash carts (RCCs) have shown promise in assisting healthcare teams during medical tasks through guided object searches and task reminders. Limited exploration has been done to determine what communication modalities are most effective and least disruptive to patient care in real-world settings. To address this gap, we conducted a between-subjects experiment comparing the RCC's verbal and non-verbal communication of object search with a standard crash cart in resuscitation scenarios to understand the impact of robot communication on workload and attitudes toward using robots in the workplace. Our findings indicate that verbal communication significantly reduced mental demand and effort compared to visual cues and with a traditional crash cart. Although frustration levels were slightly higher during collaborations with the robot compared to a traditional cart, these research insights provide valuable implications for human-robot teamwork in high-stakes environments.

Problem

• Compare verbal and non-verbal robot communication in healthcare
• Assess impact on workload and attitudes in medical settings
• Evaluate effectiveness of robotic crash carts in real-world scenarios

Innovation

• Compared verbal and non-verbal robot communication
• Reduced mental demand with verbal cues
• Assessed robot impact in high-stakes healthcare