Human-Automation Interaction Strategies and Models for Life Science Applications

摘要

The objective of this research was to identify current and future approaches to the design of automated systems for life science processes, including humans in control loops, in applications such as high-throughput compound screening and high-performance analytical chemistry. The identified approaches were classified according to existing theories of human-centered automation, which provided a basis for projecting human performance implications. We provide background on the life sciences domain and established theories of types and levels of automation (LOAs) in complex human-machine systems. We describe specific forms of robotic and automated technologies used in life science applications and the general design of high-throughput screening (HTS) and analytical systems to accommodate particular process configurations. Example classifications of life science automation (LSA) schemes are presented by referring to a taxonomy of LOAs from the literature. We project the implications of these classified forms of automation on human performance on the basis of prior empirical research in other domains. A mathematical model for predicting the cost of LSA from an operator perspective is also defined to support hypotheses for future study. Finally, we identify the need for additional empirical research on human performance consequences of LSA and remedial measures, including enhanced supervisory control interface design.