Systems and methods to estimate a subject's sleep status over time by applying data-fusion algorithms to sleep data sets collected from multiple sleep data sources are disclosed. Embodiments employ Bayes' Theorem to combine sleep data from actigraphy, sleep diary, direct observation, sleep schedules, work schedules, performance tests, neurobehavioral tests and/or the like. Particular embodiments assign data error characteristics to each source, determine likelihoods of correct reporting of sleep status from each source, and apply Bayesian analysis to each source-specific likelihood to determine an overall sleep status estimate. Data error characteristics may account, without limitation, for data insertion errors, data deletion errors, and sleep timing errors. Heuristics may be also used to correct common errors found within collected sleep data and/or to infer sleep status from atypical sources of sleep data. Particular embodiments may also use the combined sleep status estimate for fatigue prediction utilizing various biomathematical fatigue models.
Bayesian Sleep Fusion