Combine sound, stages, and watch sensors into a picture you can chart over months.
You already record most nights, and the snore count has stopped surprising you. This guide goes past that. It covers how to feed the sleep-stage estimator clean data, fold in Apple Watch biometrics, read those signals together against your timeline, and pull everything into a spreadsheet so you can chart the trend across weeks and months. Treat every number here as a personal estimate. None of it is a clinical reading. The point is to spot patterns in your own data and ask better questions.
Sleep stages in Snore Timeline come from sound. The app listens to your breathing rhythm, how regular it is, and your movement, then estimates whether you're in Light, Deep, or REM sleep, or Awake. Steady, metronome-like breathing points to Deep sleep, moderate regularity to Light, and more irregular breathing to REM. Since the whole estimate rides on hearing your breath, your setup decides how good the data is.
A few things give the estimator the clearest signal:
Longer recordings sharpen the estimate, since several hours give the app more complete sleep cycles to look at. How each signal maps to a stage is covered in Sleep Stages, and the hypnogram section explains how to read the stage chart.
If you keep seeing long Silence bands, your breathing is coming through too soft. Move the phone closer, switch to Standard quality for richer audio, and cut one source of room noise. Each change gives the stage estimator more to work with.
An Apple Watch adds a second, sensor-based view that audio can't reach. When a watch reports sleep-stage data for the night, Snore Timeline uses the watch's Deep and REM percentages for your sleep score in place of its own audio estimates, since a wrist sensor measures those stages more accurately. Without a watch, the app falls back to its breathing and movement estimates.
A paired watch also adds biometrics to your summary and your export:
All of this comes through Apple Health. Snore Timeline reads watch biometrics from Health, and it works fully with microphone access alone, so the watch is an extra and never a requirement. Health and other permissions only come up when you turn those features on. Setup steps, the full biometrics list, and notes on other wearables are in Apple Watch & Biometrics, with details on the data exchange in the Apple Health and other wearables sections.
One signal on its own tells you very little. The value comes from reading them together for a single night, then doing that night after night. Work through the summary in this order:
Snore Timeline also keeps a Sleep Bank against a 7-hour nightly goal, so you can see sleep debt building up instead of judging one night. Pair that with the weekly trends view and your sleep deficit to read the direction over time instead of reacting to one rough night.
The in-app trends answer most questions, but a spreadsheet lets you chart your own metrics and join nights to anything you track outside the app. Snore Timeline exports your data as CSV files bundled in one ZIP. Build the export like this:
For charting trends across many nights, the Nightly Summary CSV is your main table. It has one row per night, with columns including Night, Sleep Score, Sleep Efficiency, Total Sleep (s), Time to Sleep (s), Light Sleep (s), Deep Sleep (s), REM Sleep (s), Silence (s), Awake (s), WASO (s), Awakenings, Avg Respiratory Rate (bpm), Episode Count, Loudest Peak (dB), Average Peak (dB), Total Snore Signals, Total Gasp Events, Total Cough Events, Total Sleep Talking Events, and Total Breathing Disruptions. Durations are in seconds, so divide by 3600 to chart hours.
The supporting files let you go finer-grained:
Timestamps are ISO 8601 with timezone (for example 2024-01-15T22:30:45-08:00) and night identifiers are plain YYYY-MM-DD dates, which sort and filter cleanly. To chart a trend, put Night on the x-axis and the metric you care about on the y-axis. Sleep Score over 90 days, Total Breathing Disruptions per week, or Deep Sleep as a percentage of Total Sleep. The full column reference and audio-bundling options are in Export & Sharing, and the export report section covers building the file.
Automate the pull. Build a Shortcut that opens the export on a schedule so your spreadsheet stays current without you doing it by hand. See Siri, Shortcuts & Widgets.
Every metric in this guide is an estimate for your own insight. None of it is a clinical measurement or a diagnosis. Snore Timeline works out stages, respiratory rate, and breathing disruptions from sound, and reads heart rate and SpO2 from a consumer wearable. Clinical sleep staging uses brain waves, eye movement, and muscle activity, which audio can't capture, so an audio-based stage estimate lands around 70 percent agreement with polysomnography as a rough figure, with no guarantee. Disruption counts from audio skip events with no audible recovery, so treat them as a conservative floor. The app doesn't diagnose sleep apnea or any condition. If your trends worry you, or you notice daytime sleepiness, morning headaches, or a partner mentions pauses in your breathing, share the recordings and your export with a healthcare provider and let them interpret it.
Read across nights. A single rough reading often comes down to a noisy room or a phone too far away, and says nothing about your sleep. The trend is what carries the signal. The accuracy notes for stages and the guidance on when stages don't appear are worth reading before you lean on any one figure.
