User, robot and automation evaluations in high-throughput biological screening processes
Noa Segall, Rebecca S. Green, David Kaber
- 发表年份
- 2006
- 引用次数
- 7
摘要
This paper introduces high-throughput screening of biological samples in life sciences, as a domain for analysis of human-robot interaction (HRI) and development of usable human interface design principles. High-throughput screening (HTS) processes involve use of robotics and highly automated analytical measurement devices to transport and chemically evaluate biological compounds for potential use as drug derivatives. Humans act as supervisory controllers in HTS processes by performing test planning and device programming prior to experiments, systems monitoring, and real-time process intervention and error correction to maintain experiment safety and output. Process errors are infrequent but can be costly. Two forms of cognitive task analysis were applied to a highly automated HTS process to address different classes of errors, including goal-directed task analysis to describe critical operator decisions and information requirements and abstraction hierarchy modeling to represent HTS process devices and automation integrated in screening lines. The outcomes of the analyses were used as bases for generating supervisory control interface design recommendations to improve existing system usefulness and usability.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002