Google Fitbit Air: Export Google Health Data and Analyze with AI

The Google Fitbit Air AI fitness tracker lets you download all your health data, such as sleep stages, heart rate, HRV, and SpO2. We’ll show you how to export the data and easily analyze it yourself using AI assistants.

What are Google Health and the Google Fitbit Air?

Google Health and the affordable Fitbit Air fitness wearable can comprehensively track all your exercise and health data. The popular tracking wristband measures heart rate, sleep stages, SpO2, skin temperature, HRV, and respiratory rate, and automatically recognizes workouts—plus it provides Cardio Load, a Readiness Score, and much more.

But what’s really exciting isn’t the device itself, but the platform behind it: Google Health consolidates data from wearables, smart scales, Apple Health, Health Connect, and—for users in the U.S.—even electronic health records in one place. And you decide what happens to this data, including the option to export it entirely via Google Takeout.

Why You Should Analyze Your Health Data Yourself

The Google Health app does show you trends, and the Health Coach provides recommendations—but both are limited to the app’s predefined views. If you want to dig deeper, you’ll benefit from the raw data export:

• Ask your own questions: “How is my sleep related to my stress level the next day?”—no standard app shows you correlations like that.
• Identify long-term trends: The app often only shows weeks or months, but your export contains your complete history since you created your account.
• Retain data sovereignty: Your data is stored locally on your device—regardless of what happens to the platform in the future.
• Combine with other data: You can merge fitness data with your calendar, nutrition logs, or work hours and analyze them cross-referentially using AI.

Important if you still have an old, unmigrated Fitbit account: On July 15, 2026, Google began deleting data from accounts that were never migrated to a Google Account. So if you have a legacy account, you shouldn’t put off exporting your data any longer.

Tutorial: Downloading Google Health Data

There are two ways to export your data—which one you choose depends on how much historical data you need. The entire process takes just a few minutes of clicking; Google handles the actual compilation of the file in the background.

Step 1: Export data using Google Takeout

The easy-to-access Google service Google Takeout provides your complete Health archive—dating back to when you created your account—as CSV files. Takeout is recommended for a comprehensive AI analysis because it gives you the longest and most complete dataset.

Here’s how to export your Google Health data:

• Open Google Takeout at takeout.google.com and sign in with your Google account.
• Click “Deselect all” and thenselect only “Google Health.”
• Select ZIPas the format and “Send download link via email” as the delivery method.
• Click “Create export” —depending on the amount of data, the process can take anywhere from a few minutes to several hours.
• You can then download the ZIP file from Google Drive.

→ Official instructions: Google Health Help on data export

Step 2: How Google Health Data Is Organized

After extracting the files, you’ll find several folders, each containing one CSV file per day. In addition, some data also includes monthly summaries.

• Sleep/ – one file per night with sleep stages (Awake, Light, Deep, REM) including timestamps
• Heart Rate/ – Heart rate measurements, sometimes recorded every 5 seconds during active phases
• Physical Activity/ – Workouts with duration, steps, calories, and heart rate zones
• Daily Activity Summary/ – Daily summaries: steps, distance, floors climbed, calories
• HRV/ – nighttime heart rate variability (on supported devices)
• SpO2 – Oxygen saturation during sleep
• Weight – Weight and BMI trends
• Many More

Example: HRV data from Google Health

Heart rate files consist of entries with a timestamp and one value per column. It’s important to understand this structure, because this is exactly how you’ll describe it to the AI.

Step 3: Analyze Google Health Data with AI

A complete Google Takeout archive can quickly contain several hundred files—which exceeds the context window of most chat tools. You can prepare the data, or the AI can do it for you.

• Pre-filter: Select a specific folder (e.g., only “Sleep/” from the last three months) and upload only those files.
• Pre-consolidate: Convert the daily data files into a single CSV file, with one day per line. This drastically reduces the data volume and can be reliably processed by any AI.

Step 4: Analyze Google Health Data with AI

Simply upload the prepared CSV file to an AI tool and briefly provide the AI with context regarding the data structure, for example:

This is an export of my Google Health sleep data (CSV).
Columns: date, minutes_awake, minutes_light, minutes_deep, minutes_REM, sleep_score.

Analyze:
1. How has my deep sleep percentage changed over the last 3 months?
2. On which days of the week do I sleep the worst?
3. Are there any anomalies or outliers I should watch out for?

Create a chart and summarize the key findings in 5 sentences.

Example: Show a histogram of heart rate variability (HRV)

Google Health actually already provides this data in a separate file for each month.

• File name: Heart Rate Variability Histogram – 2026-06-01.csv

You can have ChatGPT display this data directly. The AI briefly analyzes the data structure itself and then displays a chart of the data distribution

The more precise your prompt, the more useful the analysis—our prompt engineering guide helps you refine exactly these kinds of analysis prompts. If you’re unsure which tool is right for your use case, it’s worth taking a look at our comparison of ChatGPT and Claude.

Bonus: Automated Analysis with n8n

If you want to have your Google Health data automatically analyzed on a regular basis—say, every week—you can set this up with an n8n workflow: A trigger loads the latest exported data from Google Drive, a code node processes the data, and an LLM node generates a brief weekly report from it, which is automatically sent to you via email or Telegram.

You can find an introduction to setting up such automations in our n8n practical guide.

Result: You’ll receive a regular AI-generated health report without having to manually export and upload data every time.

Real-World Examples: How AI Analysis of Health Data Helps

In practice, such analyses often reveal patterns you would never have noticed on your own:

• Sleep Quality vs. Exercise Time: For many users, intense exercise after 8 p.m. has been shown to lead to more restless sleep—the AI can accurately identify this correlation based on months of data.
• Weekly rhythm: It’s strikingly common for the resting heart rate to rise noticeably on Sunday evenings—a sign of “Sunday night stress” ahead of the workweek.
• HRV trends as an early warning system: An HRV value that drops over several days can indicate the onset of exhaustion or a cold before you even feel any symptoms yourself.
• Seasonal effects: Activity levels and sleep duration often change more significantly across the seasons than you might think—this only becomes apparent when looking at a full year’s worth of raw data.

Data Privacy: What You Should Keep in Mind

Health data is among the most sensitive data there is. Here are a few points to consider before uploading it to an AI tool:

• Anonymize where possible: Remove your name, date of birth, and profile data from the export files before uploading them—you don’t need them for pure trend analysis.
• Local analysis as an alternative: If you want maximum control, you can also perform the analysis locally using Python (pandas, matplotlib) instead of in the cloud.

FAQ: Exporting Google Health Data and Analyzing It with AI

Do I need a Fitbit Air to use Google Health?

No. Google Health works with any device that can be connected via Health Connect or Apple Health —including older Fitbit devices, many smartwatches, and even smart scales. The Fitbit Air is simply the newest and most affordable wearable in the Google Health ecosystem.

Is exporting via Google Takeout free?

Yes, exporting via Google Takeout is free for all Google accounts. However, depending on the amount of data, it may take some time to generate the archive file.

What file format do I get when exporting?

Google Takeout provides CSV files in a complete archive structure.

Related Links

• Google Health Help: How do I export my Fitbit data?
• Google Blog: Google Health brings your data together in one place
• Official product page: Fitbit Air

Conclusion

Google Health makes it easier than ever to access your raw data—a full export takes just a few clicks in Google Takeout. But the real value comes when you analyze this data yourself using AI tools like ChatGPT, Claude, or NotebookLM, rather than relying on the pre-made dashboards. If you still have an old, unmigrated Fitbit account, don’t put off the export any longer—Google is already deleting this data.

So: Start the export, feed the data to AI, and find out what your body has been trying to tell you for a long time. Good luck with your analysis!