Modeling Fatigue Predicting Performance

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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_at_saic.com

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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

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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
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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

• 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.

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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.

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Major Consequences of Fatigue

• Three Mile Island (1979) 400 a.m. and involved
  human error.
• Chernobyl Nuclear Reactor Meltdown (1986) 130
  a.m. and involved human error.
• Exxon Valdez (1989) 1204 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.

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Benefits of Reduced Fatigue

• More capable workforce force multiplier
• Higher level of performance (higher efficiency ,
  increased productivity, fewer errors/incidents/acc
  idents)
• Fewer accidents/incidents
• Reduced absenteeism, increased availability
• Improved health
• Higher moral
• Improved safety, reduced workmans compensation
• Reduced regulatory pressure
• Improved labor relations

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ALERTNESS COGNITIVE PERFORMANCE
Daily Variations in Effectiveness
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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

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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

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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).

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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 [phone]
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Walter Reed Restricted Sleep Study SAFTE Model
(red line) Predicts the Average Results with
Precision
Restriction
Recovery
Baseline
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Accident Likelihood Increases with Decreasing
Effectiveness
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Practical Software for Implementation

• Fatigue Avoidance Scheduling Tool (FAST)
• FAST is 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.

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FAST Graphical Screen Options
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Lapses in Attention with Reduced Sleep
Successive days of reduced sleep
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Lapse Index Graph
Lapse Index probably similar to values from
PERCLOS drowsiness monitor.
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Individual VariabilityDisplay Lowest 20
percentile, for example
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BAC Scale
The effects of fatigue may be compared to the
effects of blood alcohol to calibrate the
severity of fatigue
Continuous Hours of Wakefulness FAST Effectiveness Blood Alcohol Concentration
18.5 77 0.05
21 70 0.08
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
May33(3)337-44. Dawson, D., Reid, K., 1997.
Fatigue, alcohol and performance impairment.
Nature 388, 23.
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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

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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
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Trip Plan Editor
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Summary of Effectiveness by Waypoints
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Summary of Duty Periods
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B2 Stealth Bomber
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Lounge Chair Solution for In-flight Naps
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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

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If you would like more information, call
Monitoring Fatigue and Predicting Performance

• Steven R. Hursh, Ph.D.
• Professor, Johns Hopkins University School of
  Medicine
• and
• Science Applications International Corporation,
  301-785-2341
• Hurshs_at_saic.com

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Actigraph Recording for Sleep Estimation

• Actigraph Recording Device Records whole body
  activity and permits inferences about sleep
  timing, quality and quantity.

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Actigraph and Fatigue Assessment Software (FAST)
Actigraph Recording Device
FAST Performance Assessment Tool
Ambulatory Monitoring, Inc.

• Technical Concept
• Estimates persons 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.

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Unit Fatigue Analysis System
Sensors ? Soldier Computer ? Unit Level Receiver
and Computer ? Aggregate Analysis
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Sample Flight Plan AnalysisNot an Actual Flight
Plan
Tokyo
SIN
BKK
HOU
HKG
PEK
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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

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Printable Mission TimelineUser Selectable
Features