Considerations In Physiological Metric Selection For Online Detection Of Operator State: A Case Study
Keywords
Automated decision making aid; Fatigue; Human factors; Metric selection; Supervisory control
Abstract
The development of closed-loop systems is fraught with many challenges. One of the many important decisions to be made in this development is the selection of suitable metrics to detect operator state. Successful metrics can inform adaptations in an interface’s design, features, or task elements allocated to automated systems. This paper will discuss various challenges and considerations involved in the selection of metrics for detecting fatigue in operators of unmanned aerial vehicles (UAVs). Using Eggemeier and colleague’s guidelines for workload metric selection as a basis, we review several criteria for metric selection and how they are applied to selection of metrics designed to assess operator fatigue in an applied closed-loop system.
Publication Date
1-1-2016
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
9743
Number of Pages
428-439
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/978-3-319-39955-3_40
Copyright Status
Unknown
Socpus ID
84978818215 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84978818215
STARS Citation
Wohleber, Ryan W.; Matthews, Gerald; Funke, Gregory J.; and Lin, Jinchao, "Considerations In Physiological Metric Selection For Online Detection Of Operator State: A Case Study" (2016). Scopus Export 2015-2019. 4448.
https://stars.library.ucf.edu/scopus2015/4448