This was assessed by the number of times of waking during sleep using a measurement called WASO (wake after sleep onset). When participants reported better sleep quality (PSQI)<5, Fitbit sleep showed fewer errors in the probability of staying in the deep sleep stage.įitbit Charge 2 made fewer measurement errors in the probability of sleep transition between different stages when there was less fragmentation in sleep. The study was published in JMIR mHealth and uHealth and involved the data of one night of sleep from 23 eligible participants using Fitbit charge 2 and Sleep Scope simultaneously.Įight of the participants reported a Pittsburgh Sleep Quality Index (PSQI) >5, which means that they weren’t satisfied with their sleep quality. The researchers did not find Fitbit Charge 2 suitable for studies related to sleep-stage transitions. They suggested that the accuracy of Fitbit decreases when there are more transitions between sleep stages. The researchers found that Fitbit Charge 2 underestimated transitions from one sleep stage to another, compared to a reference medical device called Sleep Scope. They also investigated the factors associated with measurement errors by the device. 4 Measuring sleep stage transitions between light sleepĪ 2019 study by researchers in Japan evaluated the accuracy of Fitbit Charge 2 in measuring sleep stage transitions between light sleep, deep sleep, and REM sleep stages (rapid eye movement).5 Accuracy of Fitbit Charge 2ĭuring sleep, we pass through several cycles of sleep, which consist of two stages of light sleep followed by a stage of deeper sleep, and finally REM sleep.Įach stage is important and changes in the percentage and duration of these stages can point to sleep disorders or the effects of certain medications. However, more than half of these studies were done in labs and participants were mostly young or middle-aged sleepers, so the results haven’t been replicated in older adults or those who have a sleep disorder. Three studies assessed the consistency of the readings from Fitbit and found that the device showed little variability, so it could be used to assess trends in sleep quality. The researchers analyzed data from eight of the studies and found that newer Fitbit models were more accurate at estimating several sleep parameters like total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO) with results that were similar to the measurements provided by polysomnography. Ten studies assessed the older models of Fitbit and five studies assessed the recent models with only three of them comparing the results to gold standard polysomnography. The researchers evaluated all published studies on the accuracy of Fitbit, and 22 papers met their selection criteria. However, their results were less specific (had more false positives) compared to a standard sleep study offered in a sleep lab. The newer models of Fitbit were also better than older models at calculating overall sleep and wake times because they don’t rely solely on the detection of motion to indicate sleep. Researchers set out to test how accurate Fitbit sleep is as a sleep tracker in a study published in the Journal of Medical Internet Research and found that the newer models of Fitbit (that could detect stages of sleep) showed better accuracy of sleep detection than older models. 3 Researchers aimed to test Fitbit’s sleep accuracy The device has become popular among adult sleepers and researchers alike because of the ease of its use, relative inexpensiveness compared to standard clinical sleep studies (polysomnography), and the ability to follow-up variability in sleep over long periods of time. More recent models use “sleep-staging” – a machine learning algorithm that incorporates measurement data and provides a detailed personalized report on sleep patterns. What the research says about Fitbit sleepįitbit is a wearable wristband that continuously monitors heart rate and body movements.
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