Predicting chronic stress among healthy females using daily-life physiological and lifestyle features from wearable sensors
- 1. School of Psychological Sciences, University of Haifa, Haifa, Israel
- 2. School of Public Health, University of Haifa, Haifa, Israel
- 3. School of Psychological Sciences, University of Haifa, Haifa, Israel; The Integrated Brain and Behavior Research Center (IBBRC), University of Haifa, Haifa, Israel
Description
This dataset containts the recordings of 129 participants that wore the Fitbit Charge 3 for seven consecutive days. Each row represent 1 minute. In this dataset you will find information regarding participants' heart rate (BPM), sleep status, steps and other features.
The file "Dict.xlsx" contains description of the different columns in the dataset.
The full description of the dataset and of the pre-processing steps can be found in Magal et.al (2022) paper: "Predicting chronic stress among healthy females using daily-life physiological and lifestyle features from wearable sensors".
For more information please contact Dr. Roee Admon radmon@psy.haifa.ac.il
Files
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The record is publicly accessible, but files are restricted to users with access.
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This dataset is available upon a reasonable request.
Please contact Dr. Admon: radmon@psy.haifa.ac.il
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