Biosignal measurement for human-robot collaboration in construction: A systematic review

Abstract

• This study aims to map biosignal measurements relevant to human-robot collaboration in the construction industry. • An overview of 42 articles is provided, focusing on biosignal types, research objectives, and associated themes. • The qualitative literature review identifies three key research themes that utilize biosignals in human-robot collaboration. • Key findings are summarized, and future research directions are proposed. With the advancement of artificial intelligence and robotic technology, human-robot collaboration (HRC) has become an emerging trend in the construction industry to alleviate the workload, improve health and safety, and conduct repetitive work using mechanical power. However, the new working paradigm involving humans and robots in a shared team introduces novel concerns, such as human factors and ergonomics and safety issues, which require dedicated consideration in addition to the pure pursuit of technological advancement. This consideration cannot be achieved until we have reliable measurement tools to capture various human states in HRC. Biosignal, a tool to non-invasively measure human psychophysiological responses from either the central or the peripheral nervous system, provides researchers with a real-time human state measurement. This review systematically examines the application of biosignal measurement in HRC in the construction industry, addressing key research questions regarding the types of biosignals utilized, the forms of HRC, and prevalent research themes. It provides a descriptive summary of existing biosignal measurement techniques, and the robots studied, alongside a qualitative analysis of literature focused on human state assessment and biosignal measurement application in terms of HRC evaluation and estimation. A conceptual knowledge framework is proposed to consolidate findings and outline future research directions, emphasizing the challenges and potential applications of biosignal measurement in HRC. The contributions of this research include an in-depth analysis of relevant literature that identifies research gaps and offers practical implications for practitioners, such as biosignal pipelines to guide measurement selection, preprocessing, and data analysis methods. By integrating human state monitoring into HRC systems, this paper aims to enhance the design of feedback-aware and adaptive robotic systems, ultimately improving safety, efficiency, and collaboration in construction environments. The insights gained from this study lay the groundwork for further research and innovation, promoting the development of human-centered HRC systems that address the evolving challenges of the construction industry.