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Assessing General Well-Being Using Facial Expressions

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Emerging Technologies for Emerging Markets

Part of the book series: Topics in Intelligent Engineering and Informatics ((TIEI,volume 11))

Abstract

Global cell-phone ownership has surpassed over 5 billion. The proliferation of cell phones offers an unprecedented opportunity for aid organizations and governments in developing countries for providing affordable medical services for everyone. The available standardized interfaces of low-cost cell-phones allow us to create powerful medical diagnostics systems. For instance, digital cameras of cell phones now provide easy to use interfaces for capturing useful information of various medical conditions. However, photographic images often contain private and sensitive personal information in its raw form thus considered unsuitable for many available online services. Therefore, there is a need for a computational algorithm for extracting anonymous, de-identified, digital features from captured images for assessing medical conditions and general personal wellbeing. We present a de-identified feature generation method, called Gaussian Hamming Distance (GHD). We show that GHD features are significantly correlated with personal wellbeing. Its low computational complexity makes it ideal to be used with low-cost mobile devices. Its prediction power is suitable for providing a variety of online services including recommending useful health information for improving general wellbeing.

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Acknowledgments

This work was supported by JCU Singapore Research Grant JCUS/003/2011/IS and a grant from the Bill & Melinda Gates Foundation through the Grand Challenges Explorations Initiative (Grant Number: OPP1032125).

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Authors and Affiliations

  1. Financial IT Academy, Singapore Management University, 80 Stamford Road, Singapore, Singapore

    John Vong

  2. School of Business (IT), James Cook University, 600 Upper Thomson Road, Singapore, 574421, Singapore

    Insu Song

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  1. John Vong
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  2. Insu Song
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Correspondence to Insu Song .

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Vong, J., Song, I. (2015). Assessing General Well-Being Using Facial Expressions. In: Emerging Technologies for Emerging Markets. Topics in Intelligent Engineering and Informatics, vol 11. Springer, Singapore. https://doi.org/10.1007/978-981-287-347-7_8

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  • DOI: https://doi.org/10.1007/978-981-287-347-7_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-287-346-0

  • Online ISBN: 978-981-287-347-7

  • eBook Packages: EngineeringEngineering (R0)

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