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Circadian rhythms are physiological and behavioural processes that typically recur over 24-h periods. Researchers show that circadian disruption, a marked break in normal 24-h cycles of circadian rhythms, can cause serious health problems. It could lead to critical illness, cancer, stress, myocardial infarction, diabetes, hypertension and arrhythmias. Today, circadian rhythms are monitored using blood, salivary and urine hormone tests, such tests are not practical at home and do not provide continuous real-time monitoring. Combining signal processing and artificial intelligence with commercial sensors embedded in smartwatches or clothes that measure physiological and behavioral attributes offers unprecedented and as yet unexplored opportunities to monitor circadian rhythms in real time. This paper presents the initial steps towards the development of a model for real-time monitoring of the circadian rhythms. This model will contribute to transform medicine from primarily intervention-focused to predictive and preventative. Preliminary analysis shows promising results to automatically classify cortisol levels as high or low, based on behavioral and physiological signals monitored by non-invasive wearable sensors. |
