Evaluation of SmartSleep Technology for Improving the Efficiency and Restorative Quality of Sleep in Healthy Adults in Order to Mitigate Cognitive Performance Deficits Due to Sleep Restriction and Emergency Awakenings
Phase: NA
Conditions: Sleep
Sponsor: University of Pennsylvania

 
Study Title: Evaluation of SmartSleep Technology for Improving the Efficacy and Restorative 
Quality of Sleep in Healthy Adults in Order to Mitigate Cognitive Performance 
Deficits Due to Sleep Restriction and Emergency Awakenings 
 
NCT number: NCT03911154 
 
Date: 8/29/2022 
 
 

 
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Study Title:  Evaluation of SmartSleep Technology for Improving the Efficacy and Restorative 
Quality of Sleep in Healthy Adults in Order to Mitigate Cognitive Performance 
Deficits Due to Sleep Restriction and Emergency Awakenings  
 
Study Protocol and Statistical Analysis Plan 
 
BACKGROUND 
Sleep Duration and Sleep Quality in Spaceflight 
Adequate healthy sleep is essential in spaceflight to ensure astronauts maintain a high 
level of cognitive performance capability and do so without undue stress. However, studies have 
consistently found that chronic sleep restriction (i.e., sleep durations <6.5h) and astronauts’ 
perceptions of poor sleep quality were common in spaceflight shuttle missions (Barger et al., 
2014) and in International Space Station (ISS) missions (Barger et al., 2014; Jones et al., 2022). 
The latter study by Jones et al. (2022) yielded N=2,856 Reaction Self-Test (RST) assessments 
(i.e., RST = brief psychomotor vigilance test [PVT-B] with subjective ratings) that included n=394 
evaluations pre-flight; n=2,109 evaluations in-flight; n=353 evaluations post-flight. This extensive 
study on N=24 astronauts on ISS for 6-month missions revealed that reductions in sleep duration 
and perceived poor sleep quality on ISS were associated with decrements in astronauts’ 
performance on the brief psychomotor vigilance test (PVT-B) and increases in their perceptions 
of stress and physical exhaustion throughout the mission (Jones et al., 2022). Nearly half of the 
astronauts reported sleeping 6h/day or less on any given day in spaceflight, which is consistent 
with the earlier findings of Barger et al. (2014). When sleep duration on ISS was 6h or less per 
day, statistically significant deficits in PVT-B performance occurred (Jones et al., 2022). This 
result is consistent with Earth-based experiments showing that chronic restriction of sleep to 4h 
per night, 5h per night, or 6h per night resulted in sleep-dose-response cumulative psychomotor 
vigilance deficits, which involved statistically reliable decreases in PVT response speed and 
increases in lapses of attention, as well as deficits in cognitive speed and working memory 
performance (Dinges et al., 1997; Van Dongen et al., 2003; Belenky et al., 2003; Lim & Dinges, 
2008; Mollicone et al., 2008), and increases in sleep propensity, evident in decreasing sleep 
latency (Carskadon & Dement, 1981). Importantly, these neurobehavioral performance deficits 
become progressively worse as sleep restriction to below 7h per day continued across 
consecutive days. 
Sleep Medication Use in Spaceflight 
Historically, NASA physicians have prescribed sleep medications to address sleep deficits 
in spaceflight, but among other concerns articulated by Barger et al. (2014), the use of hypnotic 
medications in space can pose a risk to astronauts’ performance capability on awakening, 
especially in the event of an emergent awakening, that is, an emergency alarm requiring 
astronauts to perform at a high level within 30 seconds of the alarm. These concerns have been 
supported by a ground-based, double-blind, placebo-controlled study of zolpidem and zaleplon 
intake pre-sleep to assess their adverse effects on various cognitive tasks in N=34 astronauts, 
astronaut candidates, and flight controllers at NASA JSC (Johnston et al., 2015; Dinges et al., 
2018). Results showed that pre-sleep ingestion of sleep medications, especially 10-mg zolpidem, 
posed a substantial risk to performance at emergent awakenings from sleep (Johnston et al., 
2015; Dinges et al., 2018). 
SmartSleep Slow-Wave EEG Enhancement Could Mitigate Some of the Effects of Chronic Sleep 
Loss in Spaceflight 
There is a need for a technology that can improve sleep quality in space and biologically 
maximize the performance benefits of limited sleep duration, without unduly affecting the ability of 
astronauts to awaken abruptly due to an in-flight emergency. Studies have found that 
enhancement of EEG slow waves during sleep increased subsequent cognitive performance 

 
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(Bellesi et al., 2014; Bernardi et al., 2015; Ngo et al., 2013). Accumulating evidence suggests 
that many of the benefits of sleep are associated with sleep EEG slow waves. Slow waves reflect 
the near-synchronous alternation by millions of neurons between depolarized, active up-states, 
and hyperpolarized, inactive down-states that are thought to mediate the restorative effects of 
sleep on brain networks and cells (Tononi and Cirelli 2006). Sleep slow waves support system 
and synaptic consolidation by promoting specific patterns of neuromodulatory and electric 
activities. Subjective sleep quality is also related to the size and number of slow waves that occur 
nightly (Kecklund and Åkerstedt 1997). 
Pharmacologic approaches to improve sleep by increasing slow waves are limited by 
issues of dependence and tolerance and are often associated with residual side effects during 
subsequent wakefulness (Feld et al. 2013). Moreover, pharmacological agents cannot be 
completely washed out of the metabolic cycle in cases where an individual, like an astronaut, is 
unexpectedly awakened from sleep and needs to function quickly and accurately. 
SmartSleep is a new slow-wave enhancing technology that monitors and stages sleep 
electroencephalography (EEG) in real-time and delivers auditory stimulation during non-REM 
sleep in a closed-loop fashion at a volume that is dynamically modulated by sleep depth. 
Stimulation is stopped if the likelihood of sleep disturbance exceeds a conservative threshold. 
Pilot testing has indeed shown that the system can be used to increase the amount of slow 
waves occurring each night in a majority of individuals (Diep et al. 2020). Importantly, the 
increase in slow waves is correlated with the number of sub-awareness auditory tones played. 
SmartSleep consists of a sleep app and a headband worn during sleep that is comfortable and 
easily translatable for spaceflight. 
SmartSleep offers an alternative to the dilemma of risking the adverse effects of chronic 
sleep restriction and low sleep quality in spaceflight, versus risking the adverse effects of 
medications on sleep and waking in ever-longer duration spaceflight. If increased amounts of 
slow-wave activity in sleep via SmartSleep can translate to cognitive performance benefits and/or 
sleep quality benefits, even during periods of chronically restricted sleep time to 5h/night, it will 
offer a significant advantage over the sleep medication alternative. If this is the case, it will also 
be essential to determine whether the enhanced slow-wave activity during sleep provided by 
SmartSleep will increase sleep inertia and thereby impair cognitive performance immediately 
following an emergent awakening. It is therefore imperative that the safety of increasing slow-
wave activity be demonstrated to benefit subsequent waking cognitive performance while not 
exacerbating sleep-inertia performance deficits at emergent awakening. Operational safety 
needs to be demonstrated before the use of SmartSleep in the space program. Finally, to the 
best of our knowledge, a non-pharmacological slow-wave enhancing technology has not been 
tested in a chronic sleep restriction paradigm, despite the high prevalence of chronic sleep loss in 
astronauts and in the general population. 
OBJECTIVES 
For the above reasons, we designed a double-blind, placebo-controlled laboratory study 
of SmartSleep to determine what effect it has on daytime cognitive performance and on emergent 
awakenings from sleep in a chronic sleep restriction paradigm (i.e., 5h/night for 4 nights). This 
study is the first to evaluate slow-wave activity enhancement and its effects on performance and 
sleep inertia during sleep using a chronic sleep restriction paradigm to do the following: 
Objective 1: Evaluate whether slow wave sleep enhancement via the SmartSleep stimulus 
algorithms benefits daytime cognitive performance during a period of chronic sleep restriction as 
commonly observed during spaceflight. We assessed cognitive performance with the Cognition 
test battery (developed for NASA; Basner et al., 2015) across a range of cognitive domains and 
across a number of high fidelity spatial cognition tasks and space-operationally relevant tasks 
including Robotic On-Board Trainer (ROBoT); Six Degrees of Freedom Docking Simulator 
(6DF); and Lunar Landing Simulation. 
Objective 2: Investigate whether SmartSleep slow-wave enhancement increases 

 
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performance decrements induced by sleep inertia after an emergent awakening. 
Objective 3: Identify the best modality of acoustic stimulation in terms of slow-wave 
enhancement and cognitive performance among three different stimulation techniques: 
Continuous Fixed Interval (1 Hz, inter-tone interval stimulation), Block (5 seconds on versus 5 
seconds off), and In-Phase Adjustable (constant stimulation with tones to be delivered during 
each upstate of the slow wave). 
SPECIFIC AIMS 
The overarching goal of this project is to mitigate the effects of chronic sleep loss by 
optimizing the SmartSleep technology and demonstrating its safety at the same time. It has the 
following Specific Aims: 
Specific Aim 1: Determine whether slow-wave sleep can be enhanced via closed-loop 
auditory stimulation of EEG slow waves in healthy adult subjects using SmartSleep Headband 
technology, when sleep is restricted in duration to 5h per night over 4 consecutive nights. 
Hypothesis 1: Slow wave sleep will be enhanced via closed-loop auditory stimulation of EEG 
slow waves relative to sham stimulation, when sleep is restricted in duration to 5h per night over 
4 consecutive nights. 
Specific Aim 2: Determine whether post-sleep cognitive performance functions sensitive to 
sleep restriction can be enhanced when SmartSleep closed-loop auditory stimulation is used on 
sleep-restricted nights relative to a sham SmartSleep control condition. Hypothesis 2: Daytime 
cognitive performance will be higher after closed-loop auditory stimulation of EEG slow waves 
relative to sham stimulation, when sleep is restricted in duration to 5h per night over 4 
consecutive nights. 
Specific Aim 3: Identify the acoustic stimulation modality with maximal benefits for slow- 
wave enhancement and daytime cognitive performance, when sleep is restricted in duration to 5h 
per night over 4 consecutive nights. Hypothesis 3: One of the three acoustic stimulation 
modalities enhances EEG slow waves significantly better than the other two modalities, and is 
also associated with enhanced cognitive performance during the daytime, when sleep is 
restricted in duration to 5h per night over 4 consecutive nights. 
Specific Aim 4: Investigate systematic effects of consecutive nights of sleep restriction on 
slow-wave enhancement and daytime cognitive performance. Hypothesis 4: With increasing 
homoeostatic sleep drive induced by consecutive nights of sleep restriction, the observed slow- 
wave enhancement will mitigate some of the effects of chronic sleep loss on daytime cognitive 
performance. 
Specific Aim 5: Assess any potential adverse effects of SmartSleep utilization during sleep 
restriction, especially related to sleep inertia after emergent awakening. Hypothesis 5: Cognitive 
functioning after emergent awakenings in the acoustic stimulation conditions will be non-inferior 
relative to sham stimulation based on a non-inferiority margin of 2 lapses on the PVT-B. 
METHODS RELATED TO SPECIFIC AIMS 
SmartSleep Technology 
 
The SmartSleep technology uses two small sensors in the headband to continuously 
detect the brain’s slow wave sleep (delta/theta frequency) in real time, and a closed-loop 
algorithm customizes the timing and volume of tones to optimize the sleep pattern. Thus, the 
device uses “quiet audio tones” (sub-awareness) to increase slow waves, which can enhance 
sleep quality/depth, thereby enhancing subsequent waking cognitive performance without the 
unwanted sedating effects of medications on cognitive functions during emergency awakenings. 
Philips completed commercial development of the SmartSleep technology 
(https://www.usa.philips.com/c-e/smartsleep-advocacy.html). The Philips SmartSleep website 
states that SmartSleep is a, “Wearable sleep headband and mobile app clinically proven to 
improve the quality of your sleep”, and that it “increases your energy in the same sleep time”, it is 

 
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“for people who typically sleep <7 hours per night”, and it is a “drug-free sleep enhancement 
technology.” 
 
There is evidence that it is possible to enhance slow waves through non-pharmacological 
means, particularly with auditory stimulation (Bellesi et al., 2014; Tononi et al., 2010; Ngo et al., 
2015; Ngo et al., 2013; Papalambros et al., 2017). The enhanced slow waves are 
indistinguishable from spontaneous ones in shape, origin, distribution, and propagation (Riedner 
et al., 2011). 
 
Figure 1. a) The presence of EEG patterns (high power in the alpha 8-12 Hz and/or beta 15-30 Hz 
bands) indicative of (micro) arousals is first evaluated. If arousal-like activity is detected in the EEG 
during stimulation, the stimulation stops. If the arousal-like activity is detected outside the stimulation 
period, the onset of the next stimulation period is delayed. If no arousal-like activity is detected, then the 
system attempts to detect deep sleep based on slow wave activity (SWA) and the temporal density of 
detected slow-waves. On detection of sufficiently deep sleep, the auditory stimulation is delivered. b) 
Enhancement of slow waves when stimulation is delivered. c) SWA enhancement due to stimulation. The 
green markers indicate the time at which the stimulation was delivered 
In the last few years, Philips in collaboration with the University of Wisconsin-Madison, have 
developed a closed loop, real-time, embedded, and sleep wearable system that monitors sleep 
EEG and delivers auditory stimulation during deep sleep (N3) at a volume that is dynamically 
modulated by sleep depth. Sleep depth is estimated by taking the ratio between the EEG power 
in the 0.5 to 4 Hz band and the power in the 15 to 30 Hz band. The system consists of a headset 

 
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with a single dry EEG electrode placed on the forehead and an integrated processing unit 
embedded in the headband (Figure 1a). The reference electrode is positioned on the right 
mastoid with conductive gel to improve impedance. This system focuses on the detection of 
deep sleep (N3) and wakefulness such that it targets the stimulation to periods where sleep is 
deep and stimulation related disturbance is prevented. The N3 (wake) detection sensitivity and 
specificity are 73.5% (76.4%) and 96.9% (82.5%), respectively. The stimulation is delivered 
through speakers in a headset in the form of 50-millisecond audible tones with a one-second 
inter-tone interval. As reported in several publications (Ngo et al., 2013; Papalambros et al., 
2017; Santostasi et al., 2015), the slow-wave activity (SWA) enhancing effect is optimized by 
synchronizing the first tone to the up-phase of a detected slow-wave. If the likelihood of sleep 
disturbance exceeds a pre-established threshold, the stimulation is stopped. 
At this point, it is unclear which acoustic stimulation paradigm produces the best results in 
terms of slow-wave enhancement and cognitive performance improvement. In this study, we will 
systematically compare three acoustic stimulation modalities and sham. The four stimulation 
modalities will be provided by Phillips and are as follows: 
• 
Continuous Fixed Interval: 1 Hz inter-tone interval stimulation 
• 
Block: 5 seconds on versus 5 seconds off, and 
• 
In-Phase Adjustable: constant stimulation with tones to be delivered during each upstate of 
the slow wave. 
• 
Sham: No auditory stimulation while wearing the SmartSleep headband 
The slow wave amplitude enhancement produced by the auditory stimulation is shown in 
Figure 1b. The amplitude of deep sleep EEG clearly increases when the auditory stimulation 
(indicated by the green vertical lines in Figure 1b) is delivered. An illustration of SWA 
enhancement is shown in Figure 1c where the black curve is the SWA of a sham sleep session 
(without stimulation but while the device is worn) and the pink curve is the SWA of a sleep 
session with stimulation. The green markers (i.e., tone location) indicate the periods where the 
stimulation was delivered. 
A previous version of SmartSleep was tested in a study supported by the Australian 
Cooperative Research Center for alertness, safety and productivity. The results of this study 
(Diep et al., 2020) demonstrated that >65% of participants exhibited enhanced slow wave energy 
in the stimulation condition (STIM) with an average of 28.4% increase with respect to sham. 
Furthermore, large effect sizes were observed for improved executive function (Verbal Fluency) 
and morning vigilance (PVT) following stimulation relative to sham. 
 
STUDY DESIGN 
 
The study was conducted at the University of Pennsylvania. This placebo-controlled, 
double-blind, cross-over laboratory study of SmartSleep stimulations included sleep restriction to 
5h time in bed for sleep on 4 consecutive nights, preceded by an 8h sleep adaptation night, and 
followed by a 10h recovery night (Figure 2).  
 
The proposed sample was a total of 12 subjects to be recruited and screened for their 
ability to engage in the protocol and their similarities to astronauts (e.g., age 30-55y, educational 
background, healthy, etc.). The protocol involved monitoring of sleep-wake behaviors by 
actigraphy and sleep diary 2 weeks prior to and 1 week following the 7-day laboratory protocol. 
Participants were required to remain in the laboratory for the entire 7- day and 6-night protocol for 
cognitive testing at alarm awakening from sleep (sleep inertia test battery) and throughout each 
19h waking period (full Cognition test battery every 4 hours). In addition, participants completed 
a spatial cognition battery and three tasks with operational relevance to spaceflight (Six Degrees 
of Freedom, ROBoT, and the Lunar Lander Simulator) once a day. The 6 laboratory nights 
consisted of a baseline night (8h time in bed [TIB]), 4 nights of 5h TIB (each with one of the four 
SmartSleep stimulus conditions), and a recovery night of 10h TIB at the end. Each of the 12 
subjects received one of the SmartSleep stimulus conditions (Continuous Fixed Interval, Block, 

 
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In-Phase Adjustable, and Sham) on one of the 4 sleep restriction nights, according to a balanced 
orthogonal Latin Square design. This was a fully within-subjects design with high statistical power 
for the given sample size. This allowed us to investigate how the methodology works across the 
build-up of chronic sleep restriction (Figure 2). 
 
Subjects 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
11 
12 
Lab Day 
1 
Familiarization testing: Cognition performance testing and operational simulation testing 
Night 1 
(8h TIB) 
Adaptation to SmartSleep cap: sham stim recording nocturnal sleep EEG with no emergent 
awakening 
Lab Day 
2 
Cognition performance testing and operational simulation 
testing 
Night 2 
(5h TIB) 
Sham Stim 1 Stim 2 Stim 3 Sham Stim 1 Stim 2 Stim 3 Sham Stim 1 Stim 2 Stim 3 
Emergent Awakening (Sleep Inertia Test Bout) 
Lab Day 
3 
Cognition performance testing and operational simulation 
testing 
Night 3 
(5h TIB) 
Stim 1 Sham Stim 3 Stim 2 Stim 3 Stim 2 Stim 1 Sham Stim 2 Stim 3 Sham Stim 1 
Emergent Awakening (Sleep Inertia Test Bout) 
Lab Day 
4 
Cognition performance testing and operational simulation 
testing 
Night 4 
(5h TIB) 
Stim 2 Stim 3 Sham Stim 1 Stim 1 Sham Stim 3 Stim 2 Stim 3 Stim 2 Stim 1 Sham 
Emergent Awakening (Sleep Inertia Test Bout) 
Lab Day 
5 
Cognition performance testing and operational simulation 
testing 
Night 5 
(5h TIB) 
Stim 3 Stim 2 Stim 1 Sham Stim 2 Stim 3 Sham Stim 1 Stim 1 Sham Stim 3 Stim 2 
Emergent Awakening (Sleep Inertia Test Bout) 
Lab Day 
6 
Cognition performance testing and operational simulation 
testing 
Night 6 
(10h TIB) 
Recovery sleep: sham stim recording nocturnal sleep EEG with no emergent awakening 
Figure 2: Overview of the study design. Each of the 12 subjects underwent one adaptation night (8h TIB), 
four sleep-restriction nights (5h TIB), and one recovery night (10h TIB). Each subject was exposed to all 
four SmartSleep acoustic stimulations on the four sleep restriction nights (Stim1: Continuous Fixed 
Interval; Stim2: Block; Stim3: In-phase adjustable; and Sham) according to a balanced orthogonal Latin 
Square design. Subjects performed a sleep inertia test bout consisting of a 3-min. Psychomotor Vigilance 
Test (PVT-B) and a Digit-Symbol Substitution Test (DSST) after emergent awakenings. They also 
performed cognitive and operational testing throughout the wake periods. 
The following cognitive and spaceflight-relevant operational tasks were administered 
throughout the waking period on all days of the protocol (Figure 3): 
 
 
Figure 3: Schematic of study timeline including the sampling frequency of cognitive performance and 

 
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spaceflight operationally relevant task assessments. Black rectangles signify sleep periods with the 
nightly sleep opportunity presented in white text and wake periods are interspersed between each sleep 
period. Time of day is displayed along the bottom of the laboratory protocol timeline. Cognitive and 
spaceflight relevant operational tasks that were administered together are grouped and color-coded; each 
test grouping is associated with a colored arrow and all test administrations are positioned along the study 
timeline. Cognition, which included a DST, is colored blue; a short cognitive test battery comprised of the 
PVT, DSST, and DST are colored green, spaceflight operational tasks (ROBoT, 6DF, and Lunar Lander) 
are colored pink, and spatial cognition is colored gray. Sleep inertia test bouts were administered upon 
awakening after each sleep restricted night and are identified with text above the blue Cognition arrow. 
Descending subtraction Task (DST); Brief Psychomotor Vigilance Test (PVT); Digit-Symbol Substitution 
Test (DSST) after emergent awakenings.  
Sleep Inertia Test Bout 
The Sleep Inertia Test Bout was administered at the time of emergent awakenings, and 
consisted of two measures that were developed and validated to be sensitive to sleep inertia: the 
Brief Psychomotor Vigilance Test (PVT-B) to assess behavioral alertness and psychomotor 
speed (Basner et al., 2011); and the Digit Symbol Substitution Test (DSST) to assess cognitive 
processing throughput. In addition, we administered the Descending Subtraction Task (DST), a 
validated measure of working memory sensitive the effects of sleep loss and sleep inertia 
(Dinges, 1990; Dinges et al., 1985), as well as Visual Analog Scales (VAS) to assess subjective 
ratings of mental fatigue, tiredness, physical exhaustion, level of stress, sleep quality, and 
sleepiness. 
The PVT-B is a well-validated test based on vigilant attention and reaction time (Basner & 
Dinges, 2011; Lim & Dinges, 2008). Subjects are instructed to monitor a rectangular box on the 
screen and press the space bar as quickly as possible each time a millisecond counter appears. 
Each PVT-B reaction time is displayed for one second as feedback. Subjects are asked to 
respond as quickly as possible without committing false starts in the absence of stimuli. 
The 1.5-minute Digit Symbol Substitution Test (DSST) is validated to be sensitive to 
fatigue from sleep loss (Van Dongen et al., 2003; Dinges et al., 1985). The test is based on the 
original version in the Wechsler Adult Intelligence Scale. Subjects are presented with a legend 
that pairs unique symbols to digits (1 through 9). Symbols are then sequentially presented on the 
screen in random order. Subjects are instructed to press the corresponding number key as soon 
as possible. On each test administration, the symbol and digit correspondence is randomly 
reassigned. The DSST measures cognitive throughput based on perception and memory. 
The Descending Subtraction Test (DST) is a measure of working memory that is sensitive 
to fatigue from sleep loss and sleep inertia (Dinges, 1990; Dinges et al., 1985). The DST requires 
participants to mentally subtract numbers in a sequential fashion as quickly as possible. For 
example, if the starting number is 987, the participant subtracts nine from 987, with the difference 
being 978, the participant then subtracts eight from 978, and so on subtracting by seven, six, 
five, four, three, and two, from each difference at which point, the participant then recycles the 
subtraction sequence beginning at nine again. The DST was two minutes in duration and 
responses were entered on a keyboard. 
The Visual Analog Scales (VAS) measured subjective ratings with end points of “Mentally 
Sharp” (0) and “Mentally Fatigued” (10); “Tired” (0) and “Fresh, Ready to Go” (10); “Energetic” (0) 
and “Physically Exhausted” (10); “Not Stressed At All” (0) and “Very Stressed” (10); “Low Sleep 
Quality” (0) and “High Sleep Quality” (10); and “Not Sleepy At All” (0) and “Very Sleepy” (10).  
Cognition Test Battery 
Cognition was developed for spaceflight by Dr. Mathias Basner and his team at the 
University of Pennsylvania (Basner et al., 2015; Moore et al., 2017). It consists of 10 brief 
neuropsychological tests that cover a range of cognitive domains that are relevant for spaceflight 
and go beyond what is measured with NASA’s standard WinSCAT test battery (e.g., emotion 
recognition and risk decision-making). Fifteen unique versions of each test allow for repeated 

 
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administration of the battery. Importantly, a ground-based study in N=46 astronaut surrogate 
subjects allows for correcting for practice effects and stimulus set difficulty effects. 
Links to cerebral networks have been established with fMRI (Roalf et al., 2014). The battery was 
specifically designed for the high-performing astronaut population and was validated in both 
astronaut and astronaut surrogate populations on the ground and on the ISS (Moore et al., 
2017). Overall, the battery has been administered 7,222 times in 720 unique subjects (mean age 
35.1 years, SD 9.0 years, range 20-62 years; 71% male), including 5 astronauts on 6-month ISS 
missions, 2 astronauts on 12-month ISS missions, 8 astronauts in a ground-based study at 
Johnson Space Center (JSC), and 198 subjects in several space analog environments (including 
head-down tilt bed rest, HERA, and Antarctic research stations). The sensitivity of the battery to 
environmental stressors typically encountered on the ISS (e.g., sleep deprivation and high levels 
of CO2 [Basner et al., 2017]) has been established. Furthermore, we demonstrated that a subset 
of 3 Cognition tests (Digit Symbol Substitution, Abstract Matching, and Fractal 2-Back) was able 
to predict 30% of 6DF-docking performance variance on a task that is regularly used on the ISS 
(Johannes et al., 2016). Finally, Cognition is part of ISS Standard Measures. Therefore, 
Cognition constitutes a well-established and validated instrument for measuring spaceflight 
effects on cognitive performance. 
The Cognition battery (Basner et al., 2015; Moore et al., 2017) was administered on 
calibrated laptop computers. On average, 5 ISS astronauts required only 16.5 min to answer a 
brief survey followed by their performance on the 10 Cognition tests. We have generated 
software that automatically extracts key Cognition accuracy and speed outcomes. Facilitating 
our large database of Cognition tests, we determined loading and difficulty of individual stimuli 
via Item Response Theory (Embretson and Reise, 2000), which increases the power for our 
analyses relative to analyses based on standard accuracy outcomes (e.g., percent correct). The 
data analysis process was as follows: (1) extract one key accuracy and speed outcome for each 
test; (2) correct outcomes for practice and stimulus set difficulty effects; and (3) standardize 
outcomes based on baseline performance of all subjects (we will also generate speed, 
accuracy, and efficiency scores across cognitive domains). 
Spatial Cognition Tasks 
Spatial cognition was assessed using a variety of virtual 3D navigation tasks, which 
probes similar cognitive functions as real-world navigation and recruit similar neural networks 
(Cushman et al., 2008; Ekstrom et al., 2003; Wolbers et al., 2004). These tasks specifically 
target the hippocampus and other areas that support the encoding and retrieval of spatial 
locations, show considerable connectivity to the hippocampus, and support visuospatial 
imagery, episodic memory retrieval and self-processing operations. A subset of these tests has 
been specifically developed for in-flight assessments, which is currently prepared for flight 
certification in collaboration with Cadmos/ESA as part of the ISS experiment HypoCampus. 
This subset has been optimized relative to crew burden/compliance and scientific return, and 
with the respect to the underlying test constructs. Briefly, we employed a virtual cognitive map 
task to assess spatial memory formation (Craig et al., 2016); navigation strategies were tested 
using a modified paradigm originally proposed by Wiener et al. (2013), which allowed us to 
evaluate the selection and adoption between beacon, response cue, and spatial strategies. We 
also employed a plus maze task to specifically assess switching capabilities between 
navigational strategies (Harris et al., 2012). This paradigm has been shown to be sensitive to 
navigational switching, which is likely to be attributed to decreased functional connectivity 
between the hippocampus and pre-frontal cortex as well as dysregulation of the locus coeruleus 
noradrenergic system. To specifically target topographical memory, a digital version of the Four 
Mountains Task was performed (Chan et al., 2016; Hartley & Harlow, 2012). Path integration 
was assessed using a triangle completion task (Goeke et al., 2015). The task has been 
specifically adapted to the needs of spaceflight with respect to directions (including pitch and 
yaw), duration, velocity and complexity. In addition, a modified paradigm suggested by Wolbers 
et al. (2008) was employed to specifically assess spatial updating. Spatial orientation ability was 

 
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determined using the Perspective Taking paradigm suggested by Hegarty & Waller (2004). All 
tasks have been successfully established as part of various NASA/ESA and DLR studies (e.g. 
HERA C3, HERA C4, ESA Bed Rest ‘RSL’, ESA Bed Rest ‘Cocktail’). The frequency of tests 
administrations was optimized for each task and varied between single up to daily test 
administrations. 
Spaceflight Relevant Operational Tasks 
 
The Robotic On-Board Trainer (ROBoT) was used as an in-lab operational task. ROBoT 
is NASA’s platform for training astronauts to perform docking and grappling maneuvers using 
the Canada Arm. Proficiency with this system is mandatory for all astronauts who fly. The 
system is based on highly realistic 3D simulations of the arm and associated physics. The 
physical system involves a left-hand translational controller (x/y/z directions) and a right-hand 
rotational controller (pitch/roll/yaw), plus two laptop computer screens. The key performance 
metrics include: (i) docking position accuracy, (ii) docking orientation accuracy, (iii) total task 
time, and (iv) smoothness of approach trajectory. 
 
The Six Degrees of Freedom Docking Simulator (6DF) was used as an in-lab operational 
task. It is a high fidelity docking simulation task that has been used to investigate the 
performance of cosmonauts in the manual docking of a Soyuz spacecraft on the ISS. The 
experimental docking simulator consists of a series of docking flight tasks of varying skill level 
that have dynamic and informational equivalence to real docking maneuvers, based on 
mathematical models for real-hand control of the Soyuz spacecraft. In the evaluation of flight 
quality, there are 12 physical/mathematical parameters that describe the position and the motion 
of the spacecraft and space station with regard to each other.  
 
The Lunar Landing Simulation was used as an in-lab operational task. It includes a 
sequence of activities from the Apollo Program and the Autonomous Landing and Hazard 
Avoidance Technology (ALHAT) Project. Subjects operate the terminal descent phase of a lunar 
landing. To complete the landing there is a primary flight display, landing display, and automatic 
and manual control modes. 
STATISTICAL APPROACH 
We conducted a randomized, double-blind, cross-over laboratory study on the effects of 
the slow-wave enhancing smart sleep technology on cognitive performance during 4 consecutive 
nights of sleep restriction (5h time in bed). We compared the four auditory stimulation modalities 
(continuous fixed interval, block, in-phase adjustable, and sham) relative to their slow-wave and 
performance enhancing properties. Each subject was exposed to all 4 modalities (within-subject 
study design). We used a balanced orthogonal Latin Square design (i.e., each stimulus modality 
will appear in each of the 4 sleep restriction nights exactly once, and each modality will be 
preceded by each other modality exactly once). 
Cognitive test data were standardized to baseline performance. We used linear mixed 
effect models (in SAS version 9.4, SAS Institute, Cary, NC) with random subject intercept to 
account for the clustered nature of the data. The model included factors for stimulus modality (4 
levels), sleep restriction night (4 levels), and their interaction. We were both interested in the 
main effects (modality and sleep restriction) and their interaction, but acknowledge the limited 
power for detecting a significant interaction. If the type-III fixed effect estimate indicates a 
significant difference between groups, we compared them in post-hoc tests. The primary 
outcome was be the number of lapses (errors of commission; response times >355 ms) on the 
brief Psychomotor Vigilance Test (PVT-B) after emergent awakenings and during the day. 
Performance on the Digit Symbol Substitution (DSST), Descending Subtraction Task (DST), and 
spaceflight relevant task (ROBoT) were treated as secondary outcomes. The other cognitive 
tests (Cognition, Spatial Cognition, tasks with operational relevance for spaceflight) were treated 
as tertiary outcomes. Statistical tests for secondary and tertiary outcomes were adjusted with the 
false discovery rate method (Curran-Everet, 2000). 

 
10 
 
For the power calculations (Figure 4), we assumed a correlation between measurements 
of 0.8, and varied the standard deviation of the difference between modalities/sleep restriction 
nights from 0.8 to 1. We expect to have >80% power to find a medium effect size of 0.5 
statistically significantly different for standard deviations <0.9. 
 
 
SD 0.8 
SD 0.9 
SD 1 
100% 
 
90% 
 
80% 
 
70% 
 
60% 
 
50% 
 
40% 
 
30% 
 
20% 
 
10% 
 
0% 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1 
Effect Size 
Figure 4: Power calculations 
 
 
 
Power 1-β 

 
11 
 
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DATE:
22-Dec-2020
Institutional Review Board
TO:
David F Dinges
3600 Civic Center Blvd., 9th Floor
CC:
Carlin, Michele
Basner, Mathias
Cordoza, Makayla
Philadelphia, PA 19104
Phone: 215-573-2540
(Federalwide Assurance # 00004028)
RE:
IRB PROTOCOL#: 832679
PROTOCOL TITLE:Evaluation of SmartSleep Technology for Improving the Efficiency and
Restorative Quality of Sleep in Healthy Adults in Order to Mitigate
Cognitive Performance Deficits Due to Sleep Restriction and Emergency
Awakenings
 
SPONSOR:
NATIONAL AERONAUTICS AND SPACE ADMINISTRATION
REVIEW BOARD: IRB #2
IRB CONTINUING REVIEW: NOTICE OF APPROVAL
Dear Dr. Dinges,
The above referenced protocol was reviewed and re-approved by the
Institutional Review Board using the expedited procedure set forth in 45 CFR
46.110 on 18-Dec-2020. This study has been determined to be eligible for
expedited review category(ies) 9.
This approval is for the period 18-Dec-2020 to 17-Dec-2021.
The documents included with the application noted below are approved:
-HSERA Continuing Review, confirmation code: dcibcdad, submitted on
12/01/2020
NOTE: Approval by the IRB at this time DOES NOT constitute
authorization to initiate or continue in-person research during the
COVID-19 pandemic. Please review Guidance on Notification to the IRB
of In-Person Research Resumption During Phase II (Effective 7/13/2020)
on the IRB website here for further details: https://irb.upenn.edu. 
ONGOING REQUIREMENTS:
You must obtain IRB review and approval under 45 CFR 46 if you make
any changes to the protocol, consent form, or any other study documents
subject to IRB review requirements. Implementation of any changes

cannot occur until IRB approval has been given.
Reportable event, such as serious adverse events, deviations, potential
unanticipated problems, and reports of non-compliance must be reported
to the IRB in accordance with Penn IRB SOP RR 404.
When enrolling subjects at a site covered by the University of
Pennsylvania's IRB, a copy of the IRB approved informed consent form
with the IRB approved from/to stamp must be used unless a waiver of
written documentation of consent has been granted.
COMMITTEE APPROVALS: You are responsible for assuring and
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protocol should not commence until all relevant committee approvals have
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