Taking the sleep lab to the field: Biometric techniques for quantifying sleep and circadian rhythms in humans

Abstract

Objectives: Remarkably, the specifics of sleep along the human lineage have been slow to emerge, which is surprising given our distinct mental and behavioral capacity and the importance of sleep for individual health and cognitive performance. Largely due to difficultly of measuring sleep outside a controlled, clinical, and laboratory study in ambulatory individuals, human biologists have yet to undergo a thorough examination of sleep in ecologically diverse settings. Here, I outline the procedures and methods for generating sleep data in a broader ecological context with the goal of facilitating the integration of sleep and circadian analyses into human biology research. Methods: I describe the steps involved in participant recruitment, screening by way of survey instruments, and sample collection. In addition to describing field use of the traditional (but invasive) equipment such as the gold-standard application of electroencephalography (EEG), I demonstrate leading-edge noninvasive techniques for biometric devices (ie, wrist-worn actigraphy, ring worn arterial pulsometry) to generate sleep and circadian rhythms data. Results: I outline best approaches to process and analyze data-including variables such as sleep duration, 24-hour sleep time (ie, summation of night and day sleep), sleep efficiency, sleep fragmentation, and nonparametric circadian rhythms analysis to quantify circadian amplitude. Finally, I discuss comparative statistical methods that are optimized for the use of time-series data.Conclusions: This review serves as an introduction to the best practices for studying sleep-wake patterns in humans-with the goal of standardizing tools for launching new human sleep biology research initiatives across the globe.

A brief report of sleep and circadian rhythm quotas in a population of dog owners in North Carolina, USA

“…In conclusion, new technologies have made the study of sleep more viable, allowing for novel opportunities to study sleep and circadian rhythms in different human populations (Samson 2020, Deboer 2007. Generating data-sets characterizing sleep and circadian rhythmicity in human populations, that differ in ecology, culture, and lifestyle, is essential to understanding the role of sleep in a cross-cultural contextultimately improving the capacity to test evolutionary hypotheses about the function of human sleep (Beale, Pedrazzoli et al 2017, Samson, Crittenden et al 2017, Samson, Manus et al 2017.…”

“…With advances in biometrics and the widespread use of actigraphy outside of laboratory settings, the ability to measure the breadth of human sleep expression in multiple ecological, technological, and cultural contexts has been the hallmark of sleep research in the 21 st century (Carskadon and Dement 2005, Roenneberg 2013, Samson 2020. Despite such advances in research, we have yet to answer many fundamental questions about how human sleep varies cross-culturally and globally.…”

“…To address this challenge, work describing sleep and circadian rhythms in multiple populations dwelling in both large and small-scale societies and practicing different modes of economic production (Roenneberg 2013, Samson 2020) should be performed. Current research only contains a handful of studies that characterize sleep in discrete human populations (Roenneberg 2013, Worthman andMelby 2002), and of those, only a few also characterize circadian rhythmicity (Rock, Goodwin et al 2014, Beale, Pedrazzoli et al 2017, Samson, Crittenden et al 2017, Samson, Manus et al 2017, Smit, Broesch et al 2019.…”

Beyond Bias Minimization: Improving Intelligence with Statistical Optimization and Human Augmentation

“…Here, the IC might draw on findings from the operational community, which has developed a variety of methods for optimizing the duration and quality of sleep, as well as strategies for maintaining cognitive performance under conditions of partial and total sleep deprivation. 57 As biometric technologies rapidly advance and options for sleep tracking proliferate, 58 it is within the reach of the average consumer to track multiple aspects of their sleep including detection of blood oxygenation levels during sleep, frequency of sleep interruptions, and duration of sleep components (e.g., rapid eye movement and deep sleep). Intelligence organizations could explore ways to incentivize biometric tracking and provide health support to analysts where needed.…”

Objective and subjective measurement of sedentary behavior in human adults: A toolkit

“…Whenever these methods are used, it is advised to do visual checks (eg, producing heatmaps) to ensure that the algorithm's decisions appear sensible and apply manual corrections if necessary (Edwardson et al, 2017 ). A toolkit by Samson ( 2020 ) regarding the measurement of sleep may be the best resource for those looking to measure and remove sleep time from sedentary behavior analyses.…”