Development and evaluation of an ergonomic software package for predicting multiple-task human performance and mental workload in human-machine interface design and evaluation

被引:11
作者
Wu, Changxu [1 ]
Liu, Yili [1 ]
机构
[1] Univ Michigan, Dept Ind & Operat Engn, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会;
关键词
Ergonomics; Software package; Queueing network; Human performance; Mental workload;
D O I
10.1016/j.cie.2008.06.013
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Predicting human performance and mental workload in multiple task situations at an early stage of system design can save a significant amount of time and cost. However, existing modeling tools either can only predict human performance or require users of tools to learn a new programming language. Queueing Network-Model Human Processor (QN-MHP) is a new cognitive architecture for modeling both human performance and mental workload in multiple tasks. This paper describes the development of a Visual Basic Application in Excel (VBA) software package and an illustrative case study to evaluate its effectiveness. The software package has an easy-to-use user interface for QN-MHP that assists users of the modeling tool to simulate a dual task including definition of the tasks and interfaces by clicking buttons to select options and filling texts in a table, with no need to learn a simulation language. It allows the model user to intuitively observe the information processing state of the model during simulation, and conveniently compare the simulated human performance and mental workload for different designs. The illustrative case study showed that naive users without prior simulation language programming experience can model human performance and mental workload in a complex multitask situation within 3 min; and this software package can save 71% of modeling time and reduce 30% of modeling errors. Further developments of the VBA software package of QN-MHP are also discussed on how to make it a comprehensive proactive ergonomic design and analysis tool. Published by Elsevier Ltd.
引用
收藏
页码:323 / 333
页数:11
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