Validation of FAST Model Sleep Estimates with Actigraph Measured Sleep in Locomotive Engineers

Gertler, Judith; Hursh, Steven; Fanzone, Joseph; Raslear, Thomas

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Validation of FAST Model Sleep Estimates with Actigraph Measured Sleep in Locomotive Engineers

2012-04-01
By Gertler, Judith ; Hursh, Steven ; Fanzone, Joseph

File Language:

English

Details

Creators:

Gertler, Judith ; Hursh, Steven ; Fanzone, Joseph ; Raslear, Thomas
Corporate Creators:

QinetiQ North America, Inc. ; Institutes for Behavior Resources ; United States. Department of Transportation. Federal Railroad Administration
Corporate Contributors:

United States. Department of Transportation. Federal Railroad Administration. Office of Railroad Policy and Development
Subject/TRT Terms:
Publication/ Report Number:

DOT/FRA/ORD-12/05
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final report; Dec. 2005-Oct. 2011.
Contracting Officer:

Raslear, Thomas
Corporate Publisher:

United States. Department of Transportation. Federal Railroad Administration
Abstract:

This report presents the results of a study to validate the AutoSleep sleep prediction algorithm, which is a component of the Fatigue Avoidance Scheduling Tool (FAST). Researchers collected work and sleep data from 41 locomotive engineers by using actigraphy and daily log books and compared these data with AutoSleep predictions developed according to the log-book–recorded work periods. Comparison of the actigraphy data with model predictions on a minute-by-minute basis found an overall agreement between the two 87 percent of the time. Application of Signal Detection Theory to the data indicates that AutoSleep is biased toward underestimating daily sleep. These findings validate the sleep prediction algorithm of FAST and validate its utility for assessing fatigue risk created by typical railroad schedules.
Format:

PDF
Funding:

DFRA.080088
Download URL:

https://rosap.ntl.bts.gov/view/dot/24796/dot_24796_DS1.pdf
File Type:

[PDF - 811.07 KB]
Collection(s):

US Transportation Collection
Main Document Checksum:

urn:sha256:b6f0ce1fefced3d88cf54f230b8a59521ae47bcbdd64ae3fdd2e36ef3a51a8e4

File Language:

English

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