Enhancing User Acceptance in Human-Machine Interaction

Abstract

This study contributes to the field of user acceptance in hybrid Human-Machine Interaction (HMI) environments by establishing criteria and best practices in the exploration of factors that drive acceptance in hybrid HMI settings. This research provides a framework to guide the future development of the ABILI platform, ensuring it meets both user needs and industry demands.