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

Socpus ID

84978818215 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84978818215

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