Method for estimation of weather and weekday effects on activity behavior acquired using wearable sensors

This paper presents the importance of association investigation between weather, weekdays and unsupervised physical activities of subjects. All data were collected using wristbands and smartphones. We used methods of descriptive statistics to derive activity streams such as periodicity, intensity, s...

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Bibliographic Details
Published in:	2019 IEEE Sensors Applications Symposium (SAS) pp. 1 - 6
Main Authors:	Wolschewski, Anastasia, Ivanova, Galina, Handel, Till, Schreiber, Max
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-03-2019
Subjects:	Acceleration Activity recognition Bioinformatics Environmental factors Global Positioning System Gyroscopes Informatics Meteorology Signal processing algorithms Time series analysis Wearable sensors
Online Access:	Get full text
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Summary:	This paper presents the importance of association investigation between weather, weekdays and unsupervised physical activities of subjects. All data were collected using wristbands and smartphones. We used methods of descriptive statistics to derive activity streams such as periodicity, intensity, stable location, and velocity, and to find universal threshold values for segmentation of these streams automatically. We found that weather has an individual influence on activity patterns that can be used for personal profiling. Specifically, this influence varies significantly among subjects, depending on weekday factors.
DOI:	10.1109/SAS.2019.8706011