DocumentCode :
3706440
Title :
Smartphone app usage as a predictor of perceived stress levels at workplace
Author :
Raihana Ferdous;Venet Osmani;Oscar Mayora
Author_Institution :
CREATE-NET, Trento, Italy
fYear :
2015
fDate :
5/1/2015 12:00:00 AM
Firstpage :
225
Lastpage :
228
Abstract :
Explosion of number of smartphone apps and their diversity has created a fertile ground to study behaviour of smartphone users. Patterns of app usage, specifically types of apps and their duration are influenced by the state of the user and this information can be correlated with the self-reported state of the users. The work in this paper is along the line of understanding patterns of app usage and investigating relationship of these patterns with the perceived stress level within the workplace context. Our results show that using a subject-centric behaviour model we can predict stress levels based on smartphone app usage. The results we have achieved, of average accuracy of 75% and precision of 85.7%, can be used as an indicator of overall stress levels in work environments and in turn inform stress-reduction organisational policies, especially when considering interrelation between stress and productivity of workers.
Keywords :
"Stress","Feature extraction","Browsers","Games","Time-frequency analysis","Predictive models","Support vector machines"
Publisher :
ieee
Conference_Titel :
Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2015 9th International Conference on
Print_ISBN :
978-1-63190-045-7
Electronic_ISBN :
2153-1641
Type :
conf
DOI :
10.4108/icst.pervasivehealth.2015.260192
Filename :
7349403
Link To Document :
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