Taking the sleep lab to the field: Biometric techniques for quantifying sleep and circadian rhythms in humans. Issue 6 (30th November 2020)

• Record Type: Journal Article
• Authors: Samson, David R.
• Is Part Of: American journal of human biology. Volume 33:Issue 6(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-11-30
• Subjects: Human biology -- Periodicals; Physical anthropology -- Periodicals; Biologie humaine -- Périodiques; Anthropologie physique -- Périodiques; 612
• DOI: 10.1002/ajhb.23541
• Languages: English
• ISSNs: 1042-0533

Abstract

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.