疲労リスク管理
ワークショップ・東京
FRM/FRMS Workshop Tokyo

Predict fatigue risk in
the workplace
SAFTE-FAST is a bio-mathematical model thatpredicts changes in cognitive performance basedon the sleep/wake schedule and the body’s
internal clock.

Science and Technology

The model includes a realistic sleep predictor,
circadian performance process, circadian sleep
propensity process, sleep fragmentation process
and phase adjusting for time zone changes

Non-profit research and behavioral sciences company
with extensive experience advising government andindustry on fatigue mitigation• ISO 9001:2015 Quality Management System• EU-US Privacy Shield Framework Certified

Our Customers
Over 50 organizations worldwide○ Aviation•

Passenger Airlines•

Cargo Airlines•

Business Aviation•Air Ambulance○ Regulatory Agencies○ Ground Transportation•Rail•

Public Transit○ Military•

Air Forces•

Navy (Maritime, Air)3

- Dr. Hursh invents SAFTE model for US Army

1996
1998

Research Origins with the US Army

2001 2002 2003
2006 20072009
2011 20122016- SAFTE-FAST used by Transport Canada (Rail) to study science based scheduling- Dr. Hursh involved in US FAA ARC on 135 operations- IBR releases WebSFC online application- IBR releasees the SAFTE-FAST Console platform- FAA publishes Part 117 regulation using SAFTE-FAST as a scientific guide- FAA study validates SAFTE-FAST against PVT- FRA validates SAFTE for Type 2 schedules- SAFTE-FAST used by FAA to study science based scheduling- Commercial aviation application of VB-FAST released- FRA finds SAFTE relates schedules to an elevated risk for accidents- USN Aviation Safety Center adopts SAFTE-FAST- US DOD adopts SAFTE model as standard- USAF adopts SAFTE, VB-FAST platform introduced- Dr. Hursh invents SPM-96History of SAFTE-FAST2018 2019 2020

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Validated by FRA to predict likelihood of accidents
DOT/FRA/ORD-08/11

Hursh, Raslear, Kaye and Fanzone, 2008

Overall Human Factors Accident Risk

○ Demonstrated a clear relationship between low
performance effectiveness predicted by SAFTEFAST and risk of freight railroad accidents.
○ The risk of accidents was significantly above
chance when effectiveness was below 70.
○ Validated both SAFTE model and Auto-Sleep
predictor as actual operator sleep was not madeavailable.

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Validated by FRA to predict severity of accidents
DOT/FRA/ORD-11/13

Hursh, Fanzone and Raslear, 2011

Average Total Accidents Costs○ Demonstrated a clear relationship between low
performance effectiveness prediceted by SAFTEFAST and cost of accidents○ Average accident cost approximately $1.6 million
when average operator effectiveness was at or below
77, compared with about one-quarter of that value(approximately $400,000) when average effectivenesswas above 90.
○ Validated both SAFTE model and Auto-Sleep
predictor as actual operator sleep was not madeavailable.
○ FRA selected SAFTE-FAST as an approved model forevaluating night-time schedules under FRA passenger
hours of service regulation.
6Validated by FAA to predict aircrew performance
DOT/FAA/AM-12/12

Roma, Hursh, Mead and Nesthus, 2012

Relationship between SAFTE andPsychomotor Vigilance Test (PVT)○ Study utilized actual sleep/wake/work data from a
broadly representative sample of flight attendants○ Demonstrated a clear relationship between
performance effectiveness prediceted by SAFTEFAST and objective performance outcomes (PVT)in the field○ Reinforced the validity of the SAFTE model within
the exceptionally dynamic operational environmentof commercial aviation

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Validated against Fatigue Reports
Licati, Rodrigues, Wey, Fischer and MennaBarreto, 2014

Correlation of Effectiveness and Distribution○ Study focused on correlation between subjective
fatigue reports and quantitative predictions fromSAFTE-FAST○ Demonstrated a clear Gaussian Distribution withan average effectiveness value of 74% at the timeof fatigue reported by the pilots○ Reinforced the ability of SAFTE-FAST to predictrisk (Gaussian Distribution) and fatigue (loweffectiveness score)8

Predicted & Actual Flight Crew Sleep
Predicts the right pattern of sleep

Auto-Sleep

Auto-Sleep compared to Actigraphy○ The sleep predictor in SAFTE-FAST is known asthe Auto-Sleep algorithm○ The Auto-Sleep algorithm is a realistic sleep
predictor nearing 90% accuracy○ Auto-Sleep can be replaced with actual sleep, or
can be used in combination with actual sleep○ Seven Auto-Sleep studies have been conducted byIBR across aviation, rail and shift work industries

9The Science
Understanding the Science of Performance atWork to mitigate against fatigue impairments

The Fatigue Problem

Work ScheduleTime of Day

Sleep Debt

Long shifts, night shifts,
time-zone crossing

Working when our bodynaturally wants to sleep

Chronic fatigue driven bya constant lack ofadequate sleep

11What is Fatigue?
Fatigue is more than sleepiness and its effects are more than falling asleep○ Fatigue is a complex state characterized by a lack of alertness and it makes your mental function andphysical ability less reliable and leads to impaired performance. This is often accompanied by drowsiness.
○ A person may feel sleepy when they are impaired by fatigue, but not always.
○ Most people underestimate their own level of fatigue and how they are impaired by it.
○ A chronically fatigued person is at greater risk for accidents and is more likely to experience health problems.
○ Their is no reliable “fatigue detector” available, hence why estimating fatigue using a bio-mathematical model
like SAFTE-FAST is important.
○ The average persons does not get enough sleep to perform at peak levels.
○ Fatigue is a major hazard in the work place, responsible for errors and accidents, and has been a contributing
factor in major industrial catastrophes.

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Major Fatigue Factors
What causes us to become fatigued?
○ Time of Day: between the hours of 0000-0600.
○ Recent Sleep: less than eight hours in last 24 hours.
○ Continuous Hours Awake: more than 17 hours since last major sleep period.
○ Cumulative Sleep Debt: more than eight hours accumulation since last full night of sleep.
○ Time on Task/Work Load: continuous work time without a break or intensity of work demands.

○ SAFTE Model: All five factors interact simultaneously in non-linear relationships. A biomathematical model
simulates physiology and estimates the level of degradation in performance and provides an estimate ofoperational fatigue risk.

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Work Schedule
Folkard and Tucker, 2003

Risk of Accidents○ The risk of an accident or incident increases
dramatically in shifts longer than nine hours○ Risk increases in an approximately exponential
fashion with time on shift○ In the twelfth hour of a shift the risk is more thandouble during the first eight hours

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Time of Day
Folkard and Tucker, 2003

Successive Night Shifts○ The risk of an accident or incident increases withsuccessive night shift periods○ When compared to successive day shifts:•

Risk increases 2% on average on second night shift•

Risk increases 7% on average on third night shift•

Risk increases 17% on average on fourth night shift○ Fatigue related impairment increases between
midnight and 0600 hours○ Sleepiness is greatest between 0200 – 0600 hours

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Fatigue Effects on Performance○ Impaired logical reasoning and decision-making.
○ Impaired vigilance and attention.
○ Slowed mental operations (e.g. arithmetic).
○ Loss of situational awareness.
○ Slowed reaction time.
○ Short cuts and lapses in “optional” or self-paced
behaviors.
○ Reduced cognitive “flexibility”, impaired decisions
based on changing circumstances.

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Sleep Debt
Effect of Chronic Sleep Loss

Days of sleep loss impair performance○ Sleep Debt occurs when sleep need is not met.
○ The effects of sleep debt accumulate.
○ Sleep Debt can only be reduced by getting extrasleep.

17Subjective vs. Objective Fatigue
The difference between Emotion and Evidence○ Subjective Fatigue is an assessment of fatigue
based on or influenced by personal feelings orones own opinions.

○ Over days of chronic sleep loss:•Performance is impaired with days of sleep loss.

•Subjective reports underestimate impairment
measured in objective testing.

Subjective
Subjective Sleepiness (KSS)

PVT Performance Lapses○ Humans are not the best evaluators of their own
alertness state and can misjudge their own
impairment.

Performance Worsens○ Objective Fatigue is an evidence-based
assessment of fatigue which is based on facts.

ObjectiveBL24681012 14

Days of Sleep
Restriction

BL24681012 14

Days of Sleep
Restriction

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Solution

Predict

ReactLearn

Identify Fatigue

Mitigate Fatigue

Improve Scheduling
Practices

Predict. React. Learn.

19Concept of Mature Fatigue Modeling Approach (Aviation)
IATA: Uses and Limitations of Biomathematical Fatigue Models

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Iterative Fatigue Analysis Approach vs. Optimization Approach
Predictive and proactive fatigue risk management approaches in commercial aviation(Rangan et al. 2020)

Iterative Approach (SAFTE-FAST)

Optimization Approach○ Schedules that produce high levels of performanceare preserved.

○ Potential to eliminate highly fatigue-inducing
schedules.

○ Identify outliers along with the cause of fatigue.
Knowing the root cause of fatigue helps guidemitigation strategies:○ Potential to eliminate highly fatigue-avoiding
schedules.

•

Adjust scheduling practices•

Educate affected crewmembers on cause of fatigueand ways to minimize the risk

○ Auditing, by regulator/labor/management: fatigue isidentified along with mitigation from a risk and acost perspective.

○ Outcomes can be a rearrangement rather than areduction of overall fatigue risk across anoperation.
○ May not achieve acceptable balance between
meeting operational demands and addressing
fatigue and safety.

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SAFTE-FAST Effectiveness Calibration
Continuous
Hours ofWakefulness

Effectiveness(% of Baseline)

Reaction Time(% increase from Baseline)

Lapse Likelihood(relative to 1 for rested)

MeanCognitive

1880

+25%

3.1

88.3

18.5

77

+30%

3.7

86.3

1975

+33%

4.0

84.5

2170

+43%

5.2

81.4

403

651

+54%

6.5

77.7

Blood Alcohol
Concentration

0.05

0.08

○ Effectiveness represents the speed of performance on the Psychomotor Vigilance Test, scaled asa percent of a fully rested person’s normal best performance○ Effectiveness is highly sensitive to fatigue, corresponds to the speed of cognitive performance andcorrelated with many other cognitive performance metrics○ US FAA has a threshold of 77 for flight and duty period evaluations• https://www.faa.gov/about/office_org/headquarters_offices/agc/practice_areas/regulations/Part117/P
art117_General/media/Final%20Flight%20Duty%20Rule.pdf
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SAFTE-FAST Sleep Reservoir Calibration
Reservoir Value

Equivalent Sleep Debt

Threshold80

6.4

19 Hours Awake

75

8.0

24 Hours Awake

72

9.0

○ The Sleep Reservoir in SAFTE-FAST represents the current level of the sleep reservoir expressed as apercent of the full capacity○ The cumulative number of hours of sleep that have been missed since the Sleep Reservoir was last at fullcapacity is represented in SAFTE-FAST as Sleep Debt

○ In SAFTE-FAST, a 75% Sleep Reservoir is the equivalence of missing a full night sleep (assumedeight hours)○ NTSB Fatigue Recommendations (Hours of Service/Scheduling): recommends eight hours of
uninterrupted sleep, therefore, a 75% Sleep Reservoir in SAFTE-FAST is an NTSB threshold23

Operational Risk
SAFTE-FAST Fatigue Hazard Mitigation Strategy

Screen for low
performance at criticalphase• Screen for anyschedule withminimum
effectiveness critical
below criterion

Check for low sleep
reservoir, excess sleep
debt or time of day• Screen for minimum
sleep reservoir
equal to or below
75% (8 hours sleepdebt)

Low ReservoirDecision• Yes. Adjust
Schedule to provide
more opportunityfor sleep

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Products & Services
Proven solutions around the Science ofPerformance at Work

SoftwareWearables

Bio-mathematical
Fatigue Modeling

Data Collection

Harmonization

Consultancy

Harmonized Modeling
Settings for Operators

Expertise in the field ofSleep Science25

SAFTE-FAST Console

Full Suite Solution○ Shift Builder for non-flight crewmembers in theairline such as mechanics and ground staff.
○ Workload data which can be incorporated with
the NASA Task Load Index (TLX) scale.
○ In-flight rest periods to allow for multiple sleep
events for multiple crewmembers.
○ Exception Based Parameters for moreaccurate modeling results.
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SAFTE-FAST Schedule Analyzer
Schedule Analysis Drilldown

Schedule Analysis Dashboard

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SAFTE-FAST Reporting
Default & Custom Reports

Data Analytics

Immediate Drill-down

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Wearable ProductZulu○ Low cost, consumer grade wearable that records
sleep events as short as 20 minutes○ Ideal for data collection studies○ Off-wrist data is easily imported into SAFTEFAST FRMS software solutions○ On-wrist sleep scoring, Off-wrist detection○ Long battery life of up to one year
○ Automatic scoring of multiple sleep periods○ Light sensor for bright light and blue light○ On-demand download to Zulu Data Extractor App29

Zulu WatchManagersEmployees○ Zulu Data Collection○ Zulu Data Extraction (iOS Application)•

Distribute Zulu prior to work event/study•

De-Identified data•

Wear Zulu for the duration of the work event/study•

Sleep Event Date•

Wear Zulu when back at base•Sleep Event Start/End•

Submit Zulu to Manager•

Sleep Duration○ IBR provides customers with:•

Sleep Efficiency•

Training on Zulu Data extraction•

Subject Briefing Package (customized)•Admin. Briefing Package (customized)•Zulu User Guide○ Zulu data can be directly imported into the SAFTEFAST Console for fatigue modeling○ Actual sleep data can be used instead of AutoSleep and can be merged with work data30

Harmonization Projects○ Compare field collected actigraphy to various
permutations of Auto-Sleep parameters in SAFTEFAST○ Identifies which set of Auto-Sleep settings best
match the actigraphy-recorded sleep that iscollected in the study population○ Results are aggregated using applications of signal
detection theory and other comparison analytics toidentify the best match, based on total sleep timeand minute-by-minute pattern of sleep/wakeaccuracy

12331

Consultancy Services
Regulatory Agencies

Shiftwork Industry○ Policy Making○ Analysis of scheduling practices○ Advisory Groups○ Data collection and surveys○ Publications○ Data analysis○ Industry Documentation○ Scheduling recommendations○ Modeling32

Expect More!
Value added services provided to ourcustomers at no additional costTraining Academy
Learning Management System

For our Customers○ Complementary tool for new employees ahead oftheir training○ Can be used as part of recurrent training○ Over 30 training courses○ Learn at your own pace when it’s convenient○ Trainers can train to on-the-job tasks instead ofbasic software concepts○ Consistent IBR messaging and course updates○ Quicker and easier onboarding34

Customer Support PortalAccessible from SAFTE-FAST

Online Resource for Customers○ Generate customer support queries directly inSAFTE-FAST’s tracking system○ Receive email updates throughout the lifecycle ofthe support query○ Rate the responsiveness and level of service of
SAFTE-FAST support staff○ Raise change requests○ Request consultancy services

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info@saftefast.com

www.saftefast.com

SAFTE-FAST