Speaker
Description
Bright light soon after waking or blue-blocking glasses in the evening are standard therapies for sleep timing problems. These approaches are grounded in circadian principles which have established that the effect of light depends on the time of the biological clock with light in the biological morning speeding up the biological clock, and light in the biological morning slowing down the biological clock. Challenges for application of these principles are that the time of the biological clock is not usually known, there are substantial differences between individuals and poor adherence.
Using established sleep-wake-light regulation principles, we have developed hierarchical coupled oscillator models with feedback that take light data as input, fit to individual sleep timing and duration data and predict circadian phase in healthy unemployed controls, people living with schizophrenia and healthy older adults. This quantitative approach highlights that sleep timing problems may be a consequence of aberrant self-selected light exposure patterns but also that individual differences in physiology matter.
We present a digital twinning approach in which light and sleep timing data are combined with mathematical models in close to real time, personalized to take account of individual differences in physiology. Behavioural nudges for appropriate light consumption could enable individuals to better align sleep and circadian rhythms to lifestyles.
