Rem Sleep Vs Deep Sleep: What's Fitbit Tracking?

Fitbit devices with heart-rate tracking can record the different stages of sleep. While asleep, the body typically cycles between two types of sleep: REM (rapid eye movement) sleep and non-REM sleep, which includes light sleep and deep sleep. Fitbit estimates sleep stages by tracking movement and heart-rate patterns. When the device senses no movement for about an hour, it assumes the wearer is asleep. It also tracks beat-to-beat changes in the heart rate, which fluctuate as the wearer transitions between light sleep, deep sleep, and REM sleep. While light sleep serves as the entry point to sleep, deep sleep occurs in the first few hours and is harder to wake from. REM sleep, associated with vivid dreams, usually comes later in the night. Fitbit's sleep-staging feature is based on research and has been validated in studies, but it is not a substitute for polysomnography, the gold standard for diagnosing sleep disorders.

How does Fitbit detect sleep stages?

Fitbit devices with heart-rate tracking can record the different sleep stages a user cycles through. Fitbit estimates sleep stages by using movement and heart-rate patterns. When the user hasn't moved for about an hour, the tracker assumes they are asleep. Additional data, such as the length of time when movements indicate sleep behaviour, help confirm the user's sleep status.

While the user sleeps, the device tracks beat-to-beat changes in their heart rate, known as heart rate variability (HRV), which fluctuates as the user transitions between light sleep, deep sleep, and REM sleep. When the user syncs their device in the morning, it uses their movement and heart rate patterns to estimate their sleep cycles from the previous night.

Fitbit's sleep researchers and the National Sleep Foundation describe the following sleep stages:

• Light sleep: This is the entry point into sleep each night as the body unwinds and slows down. During the early part of light sleep, the user may drift between being awake and asleep. Their breathing and heart rate usually decrease slightly during this stage.
• Deep sleep: This typically occurs in the first few hours of sleep. When the user wakes up feeling refreshed, they likely experienced solid periods of deep sleep the night before. During deep sleep, the body becomes less responsive to outside stimuli, and breathing and heart rate slow down.
• REM sleep: This typically follows the initial stage of deep sleep and is associated with vivid dreams. Dreams mostly occur during REM sleep, and the user's eyes move quickly in different directions. Their heart rate increases, and their breathing becomes more irregular.

Fitbit estimates sleep stages with 69% accuracy in any given 30-second time window. While this may seem low, there is no systematic bias in how much light sleep, deep sleep, or sleeplessness is estimated. Therefore, using the app for many nights will give a good sense of the different sleep stages the user typically cycles through.

How does Fitbit estimate sleep stages?

Fitbit devices with heart-rate tracking can record the different stages of sleep a user cycles through. Traditionally, sleep stages are measured in a lab using an electroencephalogram to detect brain activity, along with other systems to monitor eye and muscle activity. Fitbit estimates sleep stages in a more convenient way by using movement and heart-rate patterns.

Fitbit devices assume the user is asleep when they haven't moved for about an hour. Additional data, such as the length of time when movements indicate sleep behaviour (like rolling over), help confirm the user's sleep status. While the user sleeps, the device tracks beat-to-beat changes in their heart rate, known as heart rate variability (HRV), which fluctuates as the wearer transitions between light sleep, deep sleep, and REM sleep. In the morning, when the user syncs their device, it uses movement and heart rate patterns to estimate their sleep cycles from the previous night.

Fitbit's sleep researchers and the National Sleep Foundation describe the following sleep stages:

• Light Sleep: Serves as the entry point into sleep each night as the body unwinds and slows down. This stage typically begins within minutes of falling asleep. During the early part of light sleep, the sleeper may drift between being awake and asleep, remaining somewhat alert and able to be awoken easily. Breathing and heart rate usually decrease slightly during this stage. Light sleep promotes mental and physical recovery.
• Deep Sleep: Typically occurs in the first few hours of sleep. If the user wakes up feeling refreshed in the morning, they likely experienced solid periods of deep sleep the night before. During deep sleep, the sleeper becomes harder to awaken since their body becomes less responsive to outside stimuli. Their breathing slows down, their muscles relax, and their heart rate usually becomes more regular. Deep sleep promotes physical recovery and supports aspects of memory and learning, as well as the immune system.
• REM Sleep: The first phase of REM sleep typically occurs after the initial stage of deep sleep. REM sleep periods are usually longer during the second half of the night. During this final stage of sleep, the brain becomes more active, and dreams mainly occur. The eyes move quickly in different directions, the heart rate increases, and breathing becomes more irregular. REM sleep has been shown to play an important role in mood regulation, learning, and memory as the brain processes and consolidates information from the previous day so that it can be stored in long-term memory.

How accurate is Fitbit at estimating sleep stages?

Fitbit sleep trackers have become a popular way to monitor sleep. They provide information about the quality and duration of sleep, helping users make informed decisions about their sleep habits. However, the question remains: how accurate are they at estimating sleep stages?

Fitbit's sleep-tracking algorithm relies on motion tracking, heart rate monitoring, and machine learning to estimate sleep duration and quality. It uses accelerometers to detect movement during sleep, with the assumption that more movement indicates REM or lighter sleep, while less movement suggests deep sleep. Heart rate data is also used to estimate periods of wakefulness. Additionally, Fitbit's algorithm considers age, gender, and physical activity levels in its sleep estimation.

According to a 2017 paper published by Fitbit scientists, the watch's sensors can classify sleep stages with 69% accuracy in any given 30-second time window. While this may seem low, it's important to consider the context. Fitbit's sleep staging is correct slightly more than two-thirds of the time in these 30-second blocks, and this accuracy rate is not communicated to users within the app. If used for multiple nights, the app can provide a good sense of the user's typical sleep patterns.

However, it's worth noting that Fitbit's accuracy in estimating sleep stages has been questioned in other studies. On average, Fitbit sleep trackers tend to overestimate total sleep time by about 10% and underestimate deep sleep and REM sleep by about 20% each. As deep sleep and REM sleep are crucial for recovery and memory consolidation, this inaccuracy could impact the usefulness of the data for users.

Additionally, Fitbit's reliance on motion and heart rate tracking has limitations. It may misinterpret restless sleep as wakefulness or classify periods of stillness as sleep. Heart rate variability, which can be influenced by factors like exercise, large meals, or alcohol consumption before bed, can also affect the accuracy of sleep stage identification.

In conclusion, while Fitbit sleep trackers provide valuable insights into sleep patterns, their accuracy in estimating specific sleep stages may be lower than desired. Users should interpret the data with some caution and consider combining it with other factors, such as sleep environment and pre-sleep habits, to gain a comprehensive understanding of their sleep quality.

How does Fitbit help with sleep?

Sleep is an essential component of health, and the Fitbit can help you monitor your sleep. The Fitbit can track the quantity and quality of your sleep, and provide you with data about your sleep patterns. This can help you adjust your sleep schedule to get more rest.

The Fitbit estimates your sleep stages by using your movement and heart-rate patterns. It assumes you are asleep when you don't move for about an hour, and it uses the length of time when your movements indicate sleep behaviour to confirm your sleep status. While you sleep, it tracks the beat-to-beat changes in your heart rate, known as heart rate variability (HRV), which fluctuate as you transition between light sleep, deep sleep, and REM sleep stages. When you sync your device in the morning, it uses this data to estimate your sleep cycles from the previous night.

Fitbit's sleep researchers and the National Sleep Foundation describe the following sleep stages:

• Light Sleep: This is your entry point into sleep each night as your body unwinds and slows down. This stage typically begins within minutes of falling asleep. Your breathing and heart rate usually decrease slightly during this stage. Light sleep promotes mental and physical recovery.
• Deep Sleep: This usually occurs in the first few hours of sleep. When you wake up feeling refreshed in the morning, you likely experienced solid periods of deep sleep the night before. During deep sleep, your body becomes less responsive to outside stimuli, and your breathing slows down. Deep sleep promotes physical recovery and supports aspects of memory and learning, as well as your immune system.
• REM Sleep: This is the stage associated with vivid dreams, and it typically occurs after the initial stage of deep sleep. Dreams mainly occur during REM sleep, and your eyes move quickly in different directions. Your heart rate increases, and your breathing becomes more irregular. REM sleep has been shown to play an important role in mood regulation, learning, and memory.

In addition to tracking your sleep stages, Fitbit also offers tools to help you sleep better, such as setting a sleep schedule and bedtime reminders.

How does Fitbit's accuracy compare to other methods?

Fitbit's sleep tracking technology relies on motion tracking, heart rate monitoring, and machine learning to estimate sleep duration and quality. While this technology is impressive, it has some limitations that affect its accuracy and reliability.

Motion Tracking

Fitbits use accelerometers to detect movement during sleep. When in a deep sleep, people generally move less, while in REM sleep and lighter sleep stages, they tend to move more. However, this reliance on motion tracking can lead to misinterpretations, such as classifying periods of restless sleep as wakefulness or periods of stillness as sleep.

Heart Rate Monitoring

Fitbits monitor heart rate throughout the night to estimate periods of wakefulness. However, heart rate can vary, even during sleep, due to factors like exercise, large meals, or alcohol consumption before bed. As a result, the heart rate sensors may struggle to accurately identify sleep stages.

Machine Learning

Fitbit uses machine learning algorithms to analyse movement and heart rate data, improving its ability to distinguish between sleep stages. However, this approach is simplified compared to the methods used by sleep experts, such as electroencephalography (EEG) and polysomnography, which provide a deeper level of information.

Additional Factors

Fitbit's algorithm also considers age, gender, and physical activity levels in its sleep estimation. However, it does not take into account external factors such as room temperature, noise, or disturbances, which can significantly impact sleep quality.

Polysomnography (PSG) is considered the gold standard for diagnosing sleep disorders and conducting sleep research. It involves simultaneous electroencephalographic (EEG), electromyographic, electrooculographic, electrocardiographic, and other assessments. While PSG provides highly accurate measurements, it has some drawbacks, including an uncomfortable environment, high cost, and the need for skilled technicians.

Several studies have compared the accuracy of Fitbit sleep tracking with PSG and other methods, such as actigraphy and sleep diaries. Here's a summary of their findings:

• Overestimation of total sleep time: Fitbit tends to overestimate total sleep time by approximately 7 to 67 minutes, with an average overestimation of about 10%.
• Underestimation of wake after sleep onset (WASO): Fitbit typically underestimates WASO by approximately 6 to 44 minutes.
• No significant difference in sleep onset latency (SOL): Fitbit shows no significant difference in SOL compared to PSG.
• Overestimation of sleep efficiency (SE): Fitbit overestimates SE by approximately 2% to 15%.
• Accuracy in sleep staging: Fitbit's sleep staging accuracy varies across studies, with some reporting accuracy values between 0.69 and 0.81 for light sleep, 0.36 and 0.89 for deep sleep, and 0.62 and 0.89 for REM sleep.
• Comparison with other sleep trackers: Fitbit's accuracy is comparable to other sleep trackers like Apple Watch, Garmin watches, Oura rings, and Whoop bands. These devices generally provide passable estimates of total sleep time (~80-90% accurate) but struggle with identifying specific sleep stages (50-65% accurate).

In conclusion, while Fitbit sleep tracking may not be as accurate as PSG, it offers a reasonably accurate estimation of sleep patterns and stages for consumers. It is important to consider the limitations of Fitbit's technology and interpret the data with a critical eye, focusing on trends rather than absolute values.

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