Snore Timelineについて知っておくべきすべて
Snore Timelineのサポートページへようこそ。アプリの仕組み(いびき検出、呼吸中断、睡眠ステージの分類)と、よくある質問への詳しい情報を掲載しています。
Snore Timelineはシンプルに設計されています。アプリを開いて録音ボタンを押すと、睡眠中の音を追跡できます。電話をベッドサイドの30〜60cm程度の位置に置き、できれば充電してください。アプリは一晩中録音し、音声をリアルタイムで処理します。
オンデバイスAIで以下の睡眠音を検出・分類します:
AppleのSound Analysisフレームワークを使い、すべてデバイス上でリアルタイム処理されます。
いいえ。Snore Timelineにはアカウントやログイン、クラウドサービスはありません。すべてデバイス上でローカルに動作します。
Unlike apps that sample audio periodically, Snore Timeline analyzes your audio continuously in real-time using Apple's on-device sound classification. Every sound is processed as it happens—no data is skipped or sampled.
The AI assigns a confidence score to each detected sound. The app uses different thresholds depending on the sound type and whether you're actively using the phone or it's running in the background (when you're actually sleeping). This helps reduce false positives while maintaining accuracy.
Sounds are measured in decibels (dB SPL), with the app capable of measuring up to 105 dB. Think of it like a volume meter—the higher the number, the louder the sound. The app tracks both peak and average decibel levels for each episode.
Your entire night is displayed on a scrollable, zoomable timeline. You can navigate through your sleep session to see exactly when sounds occurred.
The timeline supports multiple zoom levels:
Tip: Hold down the zoom button to quickly zoom all the way in or out—no need to tap multiple times.
Swipe left or right on the Nightly Summary screen to move between different nights. The same gesture works on the 週間サマリー screen to navigate between weeks.
Use the calendar to jump directly to any recorded night. Nights with recordings are highlighted so you can easily find your data.
If sleep stages were detected, you'll see colored background bands on your timeline indicating which stage you were in at each point during the night. This makes it easy to correlate snoring episodes with specific sleep stages.
The 週間サマリー screen shows trends across multiple nights, allowing you to track:
This helps you identify patterns and see if lifestyle changes (sleep position, weight loss, avoiding alcohol, etc.) are making a difference.
Every time the app detects a snoring sound, it counts as one "snore signal." More signals means more snoring activity during that period.
An episode is a group of snore signals that happen close together in time. When the app detects snoring, it creates an episode. If no snoring occurs for 30 seconds, that episode ends. The next time snoring is detected, a new episode begins.
Each episode shows:
The app automatically generates descriptions based on the episode characteristics:
A breathing disruption is flagged when the app detects a specific pattern: audible breathing followed by extended silence, then a recovery sound. This may indicate pauses in breathing during sleep.
The detection requires three conditions in sequence:
Breathing disruptions appear as subtle gray-blue markers on your timeline, making it easy to spot patterns throughout the night.
This is audio analysis only—not a medical device. The app cannot diagnose sleep apnea or any other medical condition. It analyzes sound patterns, not blood oxygen levels or brain activity. If you notice frequent breathing disruptions, consider discussing the results with a healthcare professional.
Sleep Stages is a feature that estimates which sleep stage you're in at any given time throughout the night: Awake, Light Sleep, Deep Sleep, or REM (Rapid Eye Movement). These estimates appear as colored bands on your timeline and as a hypnogram chart in your nightly summary.
The app analyzes the regularity and variance of your breathing patterns captured through the microphone. After approximately 15 minutes of recording, the algorithm establishes your personal breathing baseline. It then uses research-based thresholds to classify sleep stages:
The algorithm also considers breathing rate, snoring patterns, and time of night. Deep sleep typically occurs early in the night, while REM increases toward morning.
The hypnogram is a chart that shows your progression through sleep stages across the night. Each colored band represents 5 minutes in a particular stage:
You can see how many complete sleep cycles you went through, when you had the most deep sleep, and when REM sleep occurred.
The nightly summary also shows the percentage of time you spent in each stage. A typical night's sleep might look like:
These percentages can vary based on age, health, stress levels, and other factors.
Sleep stage detection is based on published research into the relationship between breathing regularity and sleep stages. The estimates provide a useful picture of your general sleep architecture and trends over time. Research using similar audio-based methods has achieved approximately 70% accuracy when validated against polysomnography (clinical sleep studies).
Important: These are estimates from audio analysis, not clinical measurements. The app has not been validated against polysomnography and should be treated as estimates, not diagnoses. For clinical sleep analysis, consult a healthcare professional.
Sleep stage detection requires audible breathing throughout the recording. If stages aren't detected:
The sleep stage classification algorithm is informed by:
Tap any episode or moment on the timeline to play back that portion of your recording. The app includes audio enhancement to make sleep sounds easier to hear.
Tap the download button on any episode to save that audio clip to your Files app. The app combines all relevant audio segments into a single file for that episode.
You can export detailed data for any night as CSV files:
This data can be useful for tracking patterns over time or sharing with healthcare providers. CSV files can be opened in Excel, Numbers, Google Sheets, or any spreadsheet app.
Choose the quality level that fits your needs:
The app includes options to manage storage:
Keep your phone about 1-2 feet away from you for best results. Closer means louder detection, but too far away reduces accuracy—especially for capturing breathing sounds, which must be clearly audible to be detected.
Ideal setup: Place your phone on a nightstand near your bed, plugged in for charging.
Snore Timeline is optimized for overnight recording. Most users report 20-30% battery drain over 8 hours. Keeping your phone plugged in ensures uninterrupted recording.
The app supports Bluetooth audio devices including AirPods. However, for best breathing detection, the phone's built-in microphone typically provides more consistent results.
For breathing disruption detection and sleep stage classification to work effectively, your regular breathing needs to be audible to the phone's microphone. If you're a very quiet breather or the phone is too far away, breathing sounds may not be detected consistently enough to establish a baseline.
To get the most accurate sleep stage estimates:
The app only saves audio when it detects sleep-related sounds. If nothing was recorded:
Breathing disruption detection has strict requirements:
If you're getting too many or too few detections:
The app is designed to continue recording in the background. If it stopped unexpectedly:
すべての録音とデータはiPhone内にローカル保存されます。サーバーやクラウドにはアップロードされません。
いいえ。Snore Timelineは個人情報を収集・送信・保存しません。分析、追跡、アカウントもありません。
アプリのタイムライン画面から録音を削除できます。すべてのデータを完全に削除するには、デバイスからアプリをアンインストールしてください。
はい — データはあなたの管理下にあります。エクスポート機能で録音とCSVレポートを保存し、好きな方法で共有できます(メール、メッセージ、クラウド等)。
詳細は プライバシーポリシー.
ここに回答がない質問、不具合、フィードバックがあればお知らせください。すべてのメッセージを読み、できる限り迅速に返信します。
Email: meneliktucker@gmail.com
Reddit: u/Comprehensive_Tap769
不具合報告時は以下を記載してください: