On the Importance of Patient Acceptance for Medical Robotic Imaging

TL;DR

This study demonstrates that interactive verbal and gestural cues in medical robotic imaging improve patient acceptance, trust, and reduce stress, highlighting the importance of tailored human-robot interactions.

Contribution

First user study on patient acceptance of robotic ultrasound, showing the impact of interaction types on trust and stress reduction.

Findings

Verbal interactions increase trust more than gestural cues.

Interactions make the robot appear friendlier.

Heart rate data suggests reduced stress through interaction.

Abstract

Purpose: Mutual acceptance is required for any human-to-human interaction. Therefore, one would assume that this also holds for robot-patient interactions. However, the medical robotic imaging field lacks research in the area of acceptance. This work, therefore, aims at analyzing the influence of robot-patient interactions on acceptance in an exemplary medical robotic imaging system. Methods: We designed an interactive human-robot scenario, including auditive and gestural cues, and compared this pipeline to a non-interactive scenario. Both scenarios were evaluated through a questionnaire to measure acceptance. Heart rate monitoring was also used to measure stress. The impact of the interaction was quantified in the use case of robotic ultrasound scanning of the neck. Results: We conducted the first user study on patient acceptance of robotic ultrasound. Results show that verbal interactions impacts trust more than gestural ones. Furthermore, through interaction, the robot is perceived to be friendlier. The heart rate data indicates that robot-patient interaction could reduce stress. Conclusion: Robot-patient interactions are crucial for improving acceptance in medical robotic imaging systems. While verbal interaction is most important, the preferred interaction type and content are participant-dependent. Heart rate values indicate that such interactions can also reduce stress. Overall, this initial work showed that interactions improve patient acceptance in medical robotic imaging, and other medical robot-patient systems can benefit from the design proposals to enhance acceptance in interactive scenarios.