Fitbit uses machine learning algorithms to track personalized sleep information and new models show improved accuracy. However, studies show limitations compared to baseline sleep studies, with most focusing on young, healthy participants. While Fitbit may help improve sleep quality, research shows mixed accuracy compared to clinical sleep studies. Fitbit was found to be better at detecting waking during sleep and measuring time to fall asleep but did not give statistically similar results overall. Additionally, a study found that Fitbit Charge 2 underestimated sleep stage transitions. More research is needed to validate Fitbit’s accuracy, especially in older or those with sleep disorders.
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