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Modeling Fatigue Predicting Performance. Steven R. Hursh, Ph.D. Professor, Johns Hopkins University School of Medicine and Program Manager, Biomedical Modeling and Analysis Science Applications International Corporation, 301-785-2341 Hurshs@saic.com. Outline. Fatigue overview.

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modeling fatigue predicting performance

Modeling Fatigue Predicting Performance

Steven R. Hursh, Ph.D.

Professor, Johns Hopkins University School of Medicine

and

Program Manager, Biomedical Modeling and Analysis

Science Applications International Corporation, 301-785-2341

Hurshs@saic.com

outline
Outline
  • Fatigue overview.
  • Drivers of fatigue
  • Biomathematical models of fatigue and the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) Model
  • Fatigue analysis tools and the Fatigue Avoidance Scheduling Tool (FAST)
  • Soldier monitoring to assess fatigue
  • Aviation applications
operational definition
Operational Definition
  • Fatigue is a complex state characterized by a lack of alertness and reduced mental and physical performance, often accompanied by drowsiness.
  • Fatigue is more than sleepiness and its effects are more than falling asleep.

DOT Human Factors Coordinating Committee, 1998

symptoms versus root causes
Symptoms

Operational Consequences

Measurable Changes in Performance

Lapses in attention and vigilance

Delayed reactions

Impaired logical reasoning and decision-making

Reduced “situational awareness”

Low motivation to perform “optional” activities

Poor assessment of risk or failure to appreciate consequences of action

Operator inefficiencies

Symptoms versus Root Causes
  • Root Cause Analysis
  • Fatigue is one potential root cause
  • No direct measure, physiological

marker, or “blood test” for fatigue

  • However, the conditions that

lead to fatigue are well known

and

  • A fatigue model can help

evaluation and integrate the

specific conditions of an

accident to determine if fatigue

was involved.

major fatigue factors
Major Fatigue Factors
  • Time of Day: between midnight and 0600 hrs.
  • Cumulative Sleep Debt: more than eight hours accumulation.
  • Acute Sleep Debt: less than eight hours in last 24 hrs.
  • Continuous Hours Awake: more than 17 hours since last major sleep period.
  • Time on Task: continuous time doing a job without a break.
major consequences of fatigue
Major Consequences of Fatigue
  • Three Mile Island (1979): 4:00 a.m. and involved human error.
  • Chernobyl Nuclear Reactor Meltdown (1986): 1:30 a.m. and involved human error.
  • Exxon Valdez (1989): 12:04 a.m. One major cause: “The failure of the third mate to properly maneuver the vessel, possibly due to fatigue and excessive workload.”
  • Operation Desert Storm (1990): More friendly fire losses than enemy losses, many due to sleep deprivation.
benefits of reduced fatigue
Benefits of Reduced Fatigue
  • More capable workforce – “force multiplier”
    • Higher level of performance (higher efficiency , increased productivity, fewer errors/incidents/accidents)
    • Fewer accidents/incidents
    • Reduced absenteeism, increased availability
    • Improved health
    • Higher moral
  • Improved safety, reduced workman’s compensation
  • Reduced regulatory pressure
  • Improved labor relations
slide8

Sleep History and Time on Duty

Time of Day

CIRCADIAN RHYTHM

CUMULATIVE SLEEP DEBT

ALERTNESS & COGNITIVE PERFORMANCE

ALERTNESS & COGNITIVE PERFORMANCE

Daily Variations in Effectiveness

major inputs for predicting fatigue
Major Inputs for Predicting Fatigue
  • Time of Day
  • Amount, quality and timing of sleep
  • Individual factors
    • Phase of the circadian “pacemaker”
    • Individual sleep need or sensitivity to sleep loss
sources of information
Sources of Information
  • Time of day: both the clock time and the time zone – inferred from location information
  • Sleep:
    • Direct measurement
    • Infer from work pattern (AutoSleep)
  • Duty periods and Critical Events:
    • Drives sleep opportunities
    • Determines critical periods for performance prediction
  • Individual factors
    • Circadian phase: temperature or hormonal oscillations
    • Sleep need: no simple test at this time
safte
SAFTE
  • The Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) Model is based on 12 years of fatigue modeling experience and over $2.6M of US DOD investment.
  • Validated against laboratory and simulator measures of fatigue. Work place calibration is underway.
  • Now accepted by the US DOD as the common warfighter fatigue model.
  • Independently compared to six models from around the world and judged to have the least error (Fatigue and Performance Workshop, Seattle, 2002).
slide12

SLEEP

REGULATION

12

PERFORMANCE

MODULATION

Schematic of SAFTE™ Simulation Model

Sleep, Activity, Fatigue and Task Effectiveness Model

DYNAMIC

PHASE

CIRCADIAN OSCILLATORS

COGNITIVE

EFFECTIVENESS

SLEEP DEBT

FEEDBACK

LOOP

SLEEP INTENSITY

SLEEP

RESERVOIR

SLEEP ACCUMULATION

(Reservoir Fill)

INERTIA

SLEEP “QUALITY”

FRAGMENTATION

PERFORMANCE USE

(Reservoir Depletion)

POC: Steven Hursh, PhD, Tel: 410-538-2901

12

walter reed restricted sleep study safte model red line predicts the average results with precision
Walter Reed Restricted Sleep StudySAFTE Model (red line) Predicts the Average Results with Precision

Baseline

Restriction

Recovery

practical software for implementation
Practical Software for Implementation
  • Fatigue Avoidance Scheduling Tool (FAST)
  • FASTis a fatigue assessment tool using the SAFTE model
  • Developed for the US Air Force and the US Army.
  • DOT/FRA sponsored work has lead to enhancements for transportation applications.
    • Sleep estimation algorithm
    • Schedule grid data entry tool
    • Wizards and dashboard
    • Standard data file format
  • DOT field calibration underway.
fast graphical screen options

Effectiveness

Adjustable Criterion Line

Lower Percentile (e.g. 20%)

Sleep Periods in Blue

Work Periods in Red

FASTGraphical Screen Options
lapses in attention with reduced sleep
Lapses in Attention with Reduced Sleep

Successive days of reduced sleep

lapse index graph
Lapse Index Graph

Lapse Index probably similar to values from PERCLOS drowsiness monitor.

bac scale
BAC Scale

The effects of fatigue may be compared to the effects of blood alcohol to calibrate the severity of fatigue

Fatigue as predicted by FAST and the effects of alcohol are not identical.

Arnedt, J.T., Wilde, G.J., Munt, P.W., MacLean, A.W. “How do prolonged wakefulness and alcohol compare in the decrements they produce on a simulated driving task?” Accid Anal Prev., 2001 May;33(3):337-44.

Dawson, D., Reid, K., 1997. “Fatigue, alcohol and performance impairment.” Nature 388, 23.

dashboard information analysis system could report fatigue indicators

Flags are fatigue indicators

Value at point

in schedule

Criteria

Dashboard InformationAnalysis System Could Report Fatigue Indicators

Content based on fatigue analysis workshop hosted by NTSB and conducted by Drs. Mark Rosekind and David Dinges, funded by FRA Office of Safety.

  • Sleep (last 24 hrs)
  • Chronic Sleep Debt
  • Hours Awake
  • Time of Day
  • Out of Phase
  • Performance Values
    • Effectiveness
    • Mean Cognitive
    • Lapse Index
    • Reaction Time
    • Reservoir
sources of uncertainty

Percent of Error

Sources of Uncertainty
  • Incomplete work/rest history, especially sleep history
  • Differences in personal sleep physiology
    • Bio-rhythms
    • Sleep need
  • Other personal factors
    • Health
    • Medications
  • Inaccuracies in our modeling and analysis
  • Lack of knowledge about specific changes in behavior

Actigraphy

Temperature Sensing & GPS

Biomedical recordings

Continuous model improvement

Performance Monitoring

commercial interest
Commercial Interest
  • Two major airlines
  • The two largest business aviation companies
  • Two large oil companies
  • Five largest freight railroads
  • A dozen electric power companies
  • Fatigue consultants
  • Two foreign governments
if you would like more information call

Monitoring Fatigue and Predicting Performance

If you would like more information, call…………

Steven R. Hursh, Ph.D.

Professor, Johns Hopkins University School of Medicine

and

Science Applications International Corporation, 301-785-2341

Hurshs@saic.com

actigraph recording for sleep estimation
Actigraph Recording for Sleep Estimation
  • Actigraph Recording Device: Records whole body activity and permits inferences about sleep timing, quality and quantity.
actigraph and fatigue assessment software fast
Actigraph and Fatigue Assessment Software (FAST)

Actigraph Recording Device

FAST Performance Assessment Tool

Ambulatory

Monitoring, Inc.

  • Technical Concept
    • Estimates person’s actual sleep and circadian rhythm based on non-invasive measurement of activity pattern.
    • Data could be transferred to computer for fatigue assessment
    • Built-in model could gives user real-time estimate of performance effectiveness.
    • Allows user to plan future activities to maximize capability using FAST.
    • Gives commanders real-time assessment of fatigue status of entire unit
  • Current status
    • Fatigue model sufficiently accurate for generic applications.
    • Actigraphy devices are now small, reliable, and highly sensitive.
    • Planning tool is available today. Used to plan military operations and training. Used to estimate fatigue in civilian transportation operations.
    • Can accept geographic waypoints during schedule to estimate sunlight and jet lag.
unit fatigue analysis system

8

7

6

5

4

3

2

1

Aggregated analysis across individuals and units.

Permits sort of units by aggregated fatigue score.

0

A

B

C

D

E

F

G

H

I

J

Unit Fatigue Analysis System

Sensors  Soldier Computer  Unit Level Receiver and Computer  Aggregate Analysis

tools for aviation
Tools for Aviation
  • Waypoints and international airport database
  • Trip Planner
  • Zulu time and world-wide local time
  • Waypoint and critical event effectiveness summary table
  • Duty period summary table
  • Mission Timeline