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Toward a Common Metric for Risk Assessment across
Diverse Factors in Fatigue Risk Management Systems:
Quantifying Human Performance in Terms of Signal-to-Noise Ratio
Hans P.A. Van Dongen, Ph.D.Director, Sleep and Performance Research Center
Professor, Elson S. Floyd College of Medicine
Washington State University Spokane
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A Typical Problem in Fatigue Risk Management:
Assessing the System-Wide Risk from Fatigue in Coupled
Physical and Cyber Infrastructures in 24/7 Operations with
Humans in the Loop
Decision graph
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A Key Aspect of Fatigue Risk from Sleep-Deprived Humans in the Loop:
Instability in Sustained Attention
Baseline
Sleep deprivation
0 200 400 600 800 1000
response time (ms)
Lapse threshold
(500 ms)
fre
qu
en
cy
Psychomotor
Vigilance
Test
(PVT)
0
500
1000
1500
2000
0 60 120 180 240 300 360 420 480 540 600
time on task (s)
re
ac
tio
n t
ime
(m
s)
0
500
1000
1500
2000
0 60 120 180 240 300 360 420 480 540 600
time on task (s)
re
ac
tio
n t
ime
(m
s)
5 h awake (13:00)
29 h awake (13:00)
res
po
ns
e t
ime
(m
s)
res
po
ns
e t
ime
(m
s)
Psychomotor Vigilance Test
0 1 2 3 4 5 6 7 8 9 10
time on task (min)
Doran SM, Van Dongen HPA, Dinges DF. Arch Ital Biol 2001; 139: 253–267.
Satterfield BC, Van Dongen HPA. Fatigue Biomed Health Behav 2013; 1: 118–136.
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a
0
b
Diffusion Decision Model
ӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ
ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿ ӿ ӿ ӿ
Numerosity DiscriminationNumerosity
Discrimination
Sleep Deprivation Degrades Cognitive Processing
in Neuronal Circuits Involved in Task Performance
Ratcliff R, Van Dongen HPA. Psychon Bull Rev, 2009; 16(4): 742–751.
Ratcliff R, Van Dongen HPA. PNAS, 2011; 108: 11285–11290.
reaction time (ms)
freq
uen
cy
diffusion
model
simulations
diffusion
model
simulations
for the PVT
C SD
freq
ue
nc
y
diffusion model
simulations for
PVT responses
BLSD
reaction time (ms)
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Diffusion Decision Model
ӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ
ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿ ӿ ӿ ӿ
Numerosity Discrimination
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
BL SD/C REC
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
SD-easy
SD-medium
SD-harder
C-easy
C-medium
C-harder
Numerosity
Discrimination
a
0
b
Sleep Deprivation Degrades Cognitive Processing
in Neuronal Circuits Involved in Task Performance
Ratcliff R, Van Dongen HPA. Psychon Bull Rev, 2009; 16(4): 742–751.
Ratcliff R, Van Dongen HPA. PNAS, 2011; 108: 11285–11290.
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Diffusion Decision Model
ӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ
ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿ ӿ ӿ ӿ
Numerosity Discrimination
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
BL SD/C REC
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
SD-easy
SD-medium
SD-harder
C-easy
C-medium
C-harder
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
SD-easy
SD-medium
SD-harder
C-easy
C-medium
C-harder
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
Numerosity
Discrimination
a
0
b
Sleep Deprivation Degrades Cognitive Processing
in Neuronal Circuits Involved in Task Performance
Ratcliff R, Van Dongen HPA. Psychon Bull Rev, 2009; 16(4): 742–751.
Ratcliff R, Van Dongen HPA. PNAS, 2011; 108: 11285–11290.
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Diffusion Decision Model
ӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ ӿӿ ӿ ӿ
ӿ ӿ ӿ ӿӿ ӿ ӿ ӿ ӿ
ӿ ӿ ӿ ӿ ӿ ӿ ӿ ӿ
Numerosity Discrimination
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
BL SD/C REC
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
SD-easy
SD-medium
SD-harder
C-easy
C-medium
C-harder
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
SD-easy
SD-medium
SD-harder
C-easy
C-medium
C-harder
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BL SD REC
Dri
ft R
ate
Numerosity
Discrimination
a
0
b
Fatigue may make
any cognitive
processing harder
and less reliable
Ratcliff R, Van Dongen HPA. Psychon Bull Rev, 2009; 16(4): 742–751.
Ratcliff R, Van Dongen HPA. PNAS, 2011; 108: 11285–11290.
Sleep Deprivation Degrades Cognitive Processing
in Neuronal Circuits Involved in Task Performance
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A Diffusion Decision Model-Based Metric of the
Fidelity of Information Processing: PVT Signal to Noise Ratio (SNR)
1
1
2
1 1
2
1
N
i
N
i
N
i
iiiii
N
i
ii
SwwSw
SwN
SNR
Si = 1 / (RTi – C), wi = 1 / (r2 Si + 1), C = 100 ms, r2 = 196 ms,
RTi is the ith response time (in ms), and N is the number of PVT stimuli
Chavali VP, Riedy SM, Van Dongen HPA. Sleep, 2017, in press.
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8
12
16
20
24
28
32
36
40
0 6 12 18 24 30 36
Time Awake (h)
SN
R
Impact of Sleep Deprivation on PVT SNR in Laboratory Studies
Chavali VP, Riedy SM, Van Dongen HPA. Sleep, 2017, in press.
Medium effect size
( f 2 = 0.34)
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8
12
16
20
24
28
32
36
40
0 6 12 18 24 30 36
Time Awake (h)
SN
R
Impact of Sleep Deprivation on PVT SNR in Laboratory Studies
Chavali VP, Riedy SM, Van Dongen HPA. Sleep, 2017, in press.
PVT testing
with chin rest
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9
11
13
15
17
0 6 12 18 24 30 36
Time Awake (h)
LS
NR
(d
B)
A Baseline-Invariant Version of the PVT SNR Metric
- 0 dB
- –3 dB
- –6 dB
Chavali VP, Riedy SM, Van Dongen HPA. Sleep, 2017, in press.
LSNR =
10 log10(SNR)
Large effect size
( f 2 = 0.40)
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Conclusions• The LSNR metric for the PVT quantifies the fidelity of information processing
• LSNR has high sensitivity to fatigue, high degree of statistical normality, and
absence of floor and ceiling effects
• A given change in LSNR always has the same meaning regardless of absolute
values – a reduction in LSNR of 3 units (i.e., a −3 dB change) represents a
50% drop in the fidelity of information regardless of the starting point
• The SNR baseline value may therefore be freely chosen to anchor the metric
(0 dB point), which is helpful for mathematical models of fatigue
• LSNR provides a basis for calculations of the overall reliability of partially
automated operational systems with sleep-deprived humans in the loop
• As such, LSNR may be a useful tool for systems-integrated fatigue risk
management
Chavali VP, Riedy SM, Van Dongen HPA. Sleep, 2017, in press.
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Research supported by:
Office of Naval Research
Air Force Office of Scientific Research
Army Medical Research and Materiel Command
National Institutes of Health
NASA Headquarters
Department of Defense
US Naval Medical Logistics Command
Naval Postgraduate School
US Army Research Office
Department of Transportation
Federal Motor Carrier Safety Administration
Federal Aviation Administration
Transportation Research Board
Regional Airline Association
FedEx Express
Pulsar Informatics
Institutes for Behavior Resources
State of Washington
Acknowledgments