Sleep tracking apps like Sleep Cycle, Pillow, and Sleep as Android have exploded in popularity in recent years. These apps claim to track your sleep stages and patterns, providing insights into how well you’re sleeping. But how do they actually work? Let’s take a look at the technology behind sleep apps.
Tracking Movement
The primary way most sleep apps detect when you’re asleep is by tracking your movement. They use your phone’s accelerometer sensor to monitor how much you’re moving throughout the night.
When you first get into bed and set your phone on your mattress, the app records your normal movement patterns while still awake. As you begin to fall asleep, your body moves less. The app detects this decrease in motion and interprets it as you falling asleep.
Similarly, when you begin to toss and turn more as you wake up, the increased movement signals to the app that you’re now awake. By comparing your motion data to your set sleep and wake times, the app attempts to figure out when you fell asleep, woke up, and how much time you spent in bed.
Tracking Heart Rate
Some sleep apps also utilize your phone’s camera or other sensors to track vitals like your heart rate. Apps like Sleep as Android and Pillow allow you to place your finger over your phone’s camera to measure subtle color changes that indicate your blood volume.
These blood volume oscillations from each heartbeat are then used to estimate your heart rate and determine your sleep stages. A slower heart rate typically means you’re in deep sleep, while an elevated heart rate is consistent with lighter sleep stages.
Tracking Sound
Your sleep environment isn’t silent. Apps can pick up sound information using your phone’s microphone to help detect your sleep state.
Snoring and deep breathing sounds tend to occur during sleep. Your alarm going off or other disruptive noises can signal periods of wakefulness. Some apps even use machine learning algorithms to analyze sleep sounds and correlate them with sleep stages.
Using Your Bedtime and Wake Time
In addition to direct sensor data, sleep apps factor in the bedtime and wake time that you manually enter. If you tell the app you’re planning to sleep from 11pm to 7am, it will assume you’re asleep during this timeframe even if the sensor data is inconclusive.
Your desired sleep schedule provides helpful contextual information to guide the app’s algorithms in determining your actual sleep and wake periods.
Evaluating Environmental Factors
Context like temperature, light levels, weather, and other environmental conditions may also be incorporated by sleep apps.
For example, colder temperatures and complete darkness are correlated with better sleep. Loud storms or bright lights could disrupt sleep. Apps that have access to this contextual data from your phone or IoT devices can therefore make better inferences about your sleep quality.
Determining Sleep Stages
Using the data sources above, sleep apps attempt to divide your sleep session into different stages like light, deep, and REM sleep.
They typically rely on motion and heart rate patterns. More movement and higher heart rate suggests lighter sleep, while less motion and slower heart rate indicates deep sleep. REM sleep is associated with greater brain activity, so apps look for variations in heart rate.
However, consumer sleep trackers are generally not as accurate at detecting sleep stages compared to clinical sleep studies. More research is needed to improve their algorithms.
Evaluating Sleep Quality
In addition to tracking sleep duration and stages, sleep apps also generate an overall sleep quality score. This is based on a combination of:
- Total sleep duration
- Time spent in each sleep stage
- Number of nightly awakenings
- Heart rate and movement data
- Environmental factors
The app’s algorithm weighs these variables to provide an overall rating of your sleep quality, typically on a 0-100 scale. However, the exact formula used varies by app.
Providing Coaching and Tips
Sleep apps don’t just track your sleep patterns – most also provide coaching and tips to improve your sleep hygiene based on your data.
For example, if the app detects you’re tossing and turning a lot at night, it may recommend trying a new pillow or mattress. If you’re not getting enough deep sleep, it may suggest trying a sleep meditation or adjusting your nighttime routine.
The coaching features are intended to help you make better sleep-related decisions and form healthier sleep habits. However, the quality of the advice varies greatly between apps.
Analyzing Long-Term Trends
Looking at your sleep data from a single night isn’t very useful. The real value comes from analyzing long-term trends.
Sleep apps use your historical sleep data to generate reports showing your sleep patterns over weeks, months, or years. This allows you to spot changes in your average sleep duration, quality, or behavior over time.
You can use these long-term trends and insights to alter your habits and environment for better sleep. However, the accuracy of the reports depends on how consistently and correctly you’ve used the app.
Is the Data Accurate?
While sleep apps claim to track your sleep stages, movements, and patterns, how accurate and reliable is their data compared to medical sleep monitoring?
Consumer sleep trackers have several limitations:
- Motion sensing is prone to errors and may mistake stillness for sleep.
- Heart rate tracking struggles to differentiate between sleep stages.
- Environmental interference can distort data.
- The underlying algorithms are imperfect.
Overall, sleep apps can provide a rough estimate of your sleep duration, quality, and behaviors. However, their accuracy is generally 50-70% compared to medical sleep studies according to research. The data is usually directionally correct, but take the exact numbers with a grain of salt.
Privacy Concerns
Giving apps access to sensitive data like your location, microphone, camera, and movement does raise potential privacy issues. Make sure to check the app’s privacy policy and permissions. Disabling unnecessary permissions and deleting your data regularly can help minimize risks.
Conclusion
While not as accurate as medical sleep monitoring devices, consumer sleep apps leverage smartphone sensors like accelerometers, cameras, and microphones along with manual sleep log data to estimate sleep stages, quality, and patterns. The convenience and simplicity of sleep apps makes them useful for spotting overall sleep trends, but treat their accuracy with skepticism. Proceed with caution when granting sleep apps access to sensitive smartphone sensors in order to protect your privacy.
| Sleep App | Data Sources Used |
|---|---|
| Sleep Cycle | Microphone, movement, sleep log |
| Pillow | Heart rate via camera, movement, sleep environment, sleep log |
| Sleep as Android | Movement, heart rate via camera, sleep log, snoring detection |
Comparison of Sleep App Accuracy
| Sleep App | Overall Accuracy | Sleep Stage Detection Accuracy |
|---|---|---|
| Sleep Cycle | 68% | 37% |
| Pillow | 63% | 41% |
| Sleep as Android | 70% | 44% |
As the table shows, sleep apps tend to have around 50-70% overall accuracy compared to medical devices according to research studies. Their accuracy at detecting specific sleep stages like deep or REM sleep is even lower. So while the apps can provide rough estimates of your sleep, consider investing in a dedicated sleep tracker device if you want higher accuracy.
Sleep App Privacy Permissions
| Sleep App | Permissions |
|---|---|
| Sleep Cycle | Microphone, motion data |
| Pillow | Camera, location, motion data |
| Sleep as Android | Camera, microphone, motion data |
Sleep apps request access to a variety of sensitive permissions in order to track your sleep. Be selective in granting permissions and review the app’s privacy policy to ensure your data is handled securely.
Tips for Improving Sleep App Accuracy
Here are some tips for getting the most accurate sleep tracking from apps:
- Put your phone on airplane mode at night to avoid signal interference.
- Make sure no bedding blocks the microphone or camera sensors.
- Enter your sleep/wake times as accurately as possible.
- Use the app daily to establish robust sleep patterns.
- Occasionally sync data against a dedicated sleep tracker for comparison.
While consumer sleep apps have limitations, following these best practices can help optimize their accuracy and reliability.