The AI migraine tracker that listens. Voice-powered headache diary with weather predictions, barometric pressure alerts, trigger analysis, and PDF reports for your doctor. Free on iOS.
Who it is for
People living with migraines who want a faster symptom diary and useful records for medical appointments.
Problem it solves
Typing detailed symptoms during an attack is difficult, so migraine records become incomplete and patterns remain hidden.
The solution
Migraine Trail records attacks through voice, adds weather and barometric context, identifies possible triggers and exports doctor-ready reports.
What makes it unique
Voice logging is designed to capture symptoms in seconds when looking at a screen or typing may make an attack worse.
Features6 listed
Voice Logging
Log a migraine attack in under 10 seconds — no tapping, no forms. Just speak naturally and our AI captures every detail.
Weather Risk Prediction
Know your migraine risk before it hits. Migraine Trail monitors barometric pressure, humidity, and temperature changes up to 14 days ahead.
Doctor-Ready Reports
Walk into every neurology appointment prepared. Generate a clean PDF summary of your attack history, triggers, and medications in one tap.
Attack & Symptom Logging
Capture the full picture of every attack — intensity, duration, location, aura, nausea, light sensitivity, and more.
Trigger Identification
Stop guessing what's causing your migraines. Migraine Trail surfaces statistically significant trigger patterns from your own data.
Medication & Treatment Log
Track what you take, when you take it, and whether it works — so you and your doctor can fine-tune your treatment plan.
Details
Platforms
iOS
Pricing
Subscription
Built for
People living with migraines who want a faster symptom diary and useful records for medical appointments.
In IndieTools' mobile lab test on November 12, 2026, the Migraine Trail website scored 98 out of 100 (good). Largest Contentful Paint took 1.35 s, rated good. It placed #310 overall in the finalized week 2026-W45.
Measured (UTC)
LCPLargest Contentful Paint
1.35 s
Good
TBTTotal Blocking Time
40 ms
Good
CLSCumulative Layout Shift
0.000
Good
FCPFirst Contentful Paint
1.35 s
Good
Ranked #310 overall in 2026-W45, best #53.
Migraine Trail lab metrics
Speed metrics for Migraine Trail, measured November 12, 2026
Metric
Result
Status
Trend
Mobile lab testMid-range phone on a throttled 4G connection, two runs averaged. Changes compare with the run on Nov 11.
Performance score
GoodAbout the same
98 / 100
GoodAbout the same
First Contentful PaintFCP
GoodAbout the same
1.35 s
GoodAbout the same
Largest Contentful PaintLCP
GoodAbout the same
1.35 s
GoodAbout the same
Speed IndexSI
Needs improvementAbout the same
4.22 s
Needs improvementAbout the same
Total Blocking TimeTBT
GoodAbout the same
40 ms
GoodAbout the same
Cumulative Layout ShiftCLS
GoodAbout the same
0.000
GoodAbout the same
Unthrottled observationsTimed on the test machine's own fast connection, so they read lower than the lab metrics above.
Page loadLoad
34 ms faster
425 ms
34 ms faster
Server responseTTFB
About the same
2 ms
About the same
Migraine Trail performance history
56 comparable mobile lab runs since September 27, 2026. Choose a metric and a range, then move along the line to read each run.
Migraine Trail Speed ranking
Weekly Speed standing for Migraine Trail
Weekly standingLatest finalized week 2026-W45. Bests cover the last 52 finalized weeks.
Stored lab observations from controlled test runs, not real-user Core Web Vitals or a guarantee of search rankings. Weekly standings remain attached to their finalized edition.Method psi-mobile-two-sample-mean-v1, 2 samples per reading. Lab results can vary between runs.
Model difference−4. DR4 is 4 points lower than DR3.
Measured · migrainetrail.com
What do DR4, DR3 and the model difference mean?
DR4:
Ahrefs' newer model. It gives more weight to links from sites with organic search traffic and rates a subdomain on its own links.
DR3:
The previous model, shown in the Ahrefs app until 1 December 2026.
Model difference:
DR4 minus DR3 for the same domain. The models calculate differently, so this is not growth or a drop; the “since” lines compare each model with itself.
