WH2014 Session: Machine learning-based analysis of smartphone usage pattern and
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Transcript of WH2014 Session: Machine learning-based analysis of smartphone usage pattern and
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WLSACONVERGENCE SUMMIT
MACHINE LEARNING-BASED ANALYSIS OF SMARTPHONE USAGE PATTERN AND ITS ASSOCIATION WITH NEGATIVE HUMAN EMOTION
GALEN CHIN-LUN HUNG
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What you do on the smartphone predicts how
you feel.
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Our model predicts 3 negative emotions based on the smartphone
usage pattern in the past two hours, with an average accuracy rate of
83.2%
Pleasure AnxietyStress
No feature selectionSelected model
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DEMO & ABSTRACT PRESENTATION SESSION #11.4 RESEARCH ABSTRACT
MACHINE LEARNING-BASED ANALYSIS OF SMARTPHONE USAGE PATTERN AND ITS ASSOCIATION WITH NEGATIVE HUMAN
EMOTIONGALEN CHIN-LUN HUNG; PEI-CHING YANG; CHIA-CHI CHANG;
JUNG-HSIEN CHIANG
This model has a potential for real-time treatment by envisioning negative emotions
and providing preventive interventions before the users actually 'feel bad’
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WLSACONVERGENCE SUMMIT
www.wirelesshealth2014.org