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Wearable Fitness Tracker Public Domain Dataset
Mental Health & Wellness
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About
Presents minute-level output derived from Fitbit trackers, intended for open-source use in pattern recognition and analysis of physical activity data. This data was collected from thirty eligible users who provided consent via a distributed survey. It consolidates information on daily activity, heart rate, calories, intensities, steps, sleep monitoring, METs, and weight, serving as a useful resource, particularly for extending data used in the Google Data Analytics Capstone Bellabeat case study.
Columns
The dataset, exemplified by the combinedHeartrateSeconds.csv file, contains four key data points:
- Id: The unique identifier assigned to individual users.
- Date: The date of the recorded heart rate measurement, presented in YYYY-MM-DD format.
- Time: The precise time of the recording, formatted as HH:MM:SS.
- Value: The numerical heart rate measurement recorded by the device.
Distribution
This product is typically available as CSV files. The heart rate sample file provided is 71.52 MB and includes approximately 2.10 million valid records. The structure consists of four columns per record. New data is expected to be updated annually.
Usage
This data is perfectly suited for building predictive models related to health and activity patterns. It can be used for detailed analysis of user tracking behaviours and preferences, or to compare variations in output from different types of Fitbit trackers. It provides robust historical data for academic studies focusing on public health and digital wellness.
Coverage
The data collection period ranges from 03 December 2016 to 05 May 2016. Specifically, the heart rate records span from 29 March 2016 to 12 May 2016. The information was gathered from thirty consented Fitbit users, who participated via a distributed survey mechanism.
License
CC0: Public Domain
Who Can Use It
- Health Researchers: For investigating minute-level physiological responses and activity trends.
- Data Scientists: For developing algorithms focused on predicting user activity levels or heart health indicators.
- Students: Utilizing real-world wearable device data for coursework in data analytics and statistics.
Dataset Name Suggestions
- Fitbit Minute-Level Heart Rate and Activity Data (2016)
- Wearable Fitness Tracker Public Domain Dataset
- Consolidated Fitabase Activity Metrics
Attributes
Original Data Source:Wearable Fitness Tracker Public Domain Dataset
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