Fitbit Wellness Tracker Data

• Export 1: March 12, 2016 - April 11, 2016
• Export 2: April 12, 2016 - May 12, 2016

1. Daily Activity:
   • Aggregated metrics for steps, calories, and intensity.
   • Files: dailyActivity_merged.csv, dailyCalories_merged.csv, dailyIntensities_merged.csv, dailySteps_merged.csv.
2. Hourly Data:
   • Hourly breakdowns of activity and calorie burn.
   • Files: hourlyCalories_merged.csv, hourlyIntensities_merged.csv, hourlySteps_merged.csv.
3. Minute-Level Data:
   • High-resolution data in narrow and wide formats for calories, steps, intensity, and METs.
   • Files:
     • Narrow: minuteCaloriesNarrow_merged.csv, minuteIntensitiesNarrow_merged.csv, minuteStepsNarrow_merged.csv, minuteMETsNarrow_merged.csv.
     • Wide: minuteCaloriesWide_merged.csv, minuteIntensitiesWide_merged.csv, minuteStepsWide_merged.csv.
4. Heart Rate:
   • Second-by-second heart rate data for precise analysis.
   • File: heartrate_seconds_merged.csv.
5. Sleep Data:
   • Insights into sleep quality, duration, and patterns.
   • Files: minuteSleep_merged.csv, sleepDay_merged.csv.
6. Weight Logs:
   • Tracking user weight and trends over time.
   • File: weightLogInfo_merged.csv.

Who can use it:

• Health Behavior Analysis: Study routines, anomalies, and behavioral trends in activity, sleep, and heart rate.
• Machine Learning Applications: Develop predictive models for fatigue, health risks, or fitness improvements.
• Wearable Technology Research: Evaluate user engagement with fitness trackers and related behavioral insights.
• Personalized Wellness Studies: Correlate heart rate, activity levels, and sleep to derive personalized health strategies.

Usage:

1. Fitness and Wellness Trends: Uncover patterns in activity, sleep, and heart rate data.
2. Temporal Analysis: Study how routines and behaviors change over time.
3. Predictive Analytics: Build models to predict fatigue or health risks using granular data.
4. Wearable Insights: Enhance the understanding of Fitbit devices and their impact on user health.

License

📌 Acknowledgment

Original Source:

• Zenodo: Fitbit Data Archive

• Julen Aranguren
• Anastasiia Chebotina