Temporal organisation of molecular and physiological processes is driven by environmental and behavioural cycles, as well as by self-sustained molecular circadian oscillators. Quantification of phase, amplitude, period, and disruption of circadian rhythms is essential for understanding their contribution to sleep-wake disorders, social jet-lag, inter-individual differences in entrainment and the development of chrono-therapeutics.

Traditionally, assessment of the human circadian system, and the output of the SCN in particular, required collection of long time series of univariate markers such as melatonin or core body temperature. Data were collected in specialised laboratory protocols designed to control for environmental and behavioural influences on rhythmicity. These protocols are time-consuming, expensive, and are not practical for assessing circadian status in patients or in participants in epidemiologic studies.

Novel approaches for assessment of circadian parameters of the SCN or peripheral oscillators have been developed. They are based on machine learning or mathematical model-informed analyses of features extracted from one or a few samples of high dimensional data such as transcriptomes, metabolomes, long term simultaneous recording of activity, light exposure, skin temperature, and heart rate, or in vitro approaches. Here, we review whether these approaches successfully quantify parameters of central and peripheral circadian oscillators as indexed by gold standard markers. While several approaches perform well under entrained conditions when sleep occurs at night, the methods either perform worse in other conditions such as shift work, or they have not been assessed under any conditions other than entrainment and thus we do not yet know how robust they are.

Novel approaches for the assessment of circadian parameters hold promise for circadian medicine, chrono-therapeutics, and chrono-epidemiology. There remains a need to validate these approaches against gold standard markers, in individuals of all sexes and ages, in patient populations, and, in particular, under conditions in which behavioural cycles are displaced.