Opportunistic and context-aware affect sensing on smartphones: the concept, challenges and opportunities

Rana, Rajib and Hume, Margee and Reilly, John and Jurdak, Raja and Soar, Jeffrey ORCID: https://orcid.org/0000-0002-4964-7556 (2016) Opportunistic and context-aware affect sensing on smartphones: the concept, challenges and opportunities. IEEE Pervasive Computing, 15 (2). pp. 60-69. ISSN 1536-1268


Opportunistic affect sensing offers unprecedented potential for capturing spontaneous affect, eliminating biases inherent in the controlled setting. Facial expression and voice are two major affective displays, but most affect sensing systems on smartphones avoid them due to extensive power requirements. Encouragingly, due to the recent advent of low-power DSP coprocessor and GPU technology, audio and video sensing are becoming more feasible on smartphones. To utilize opportunistically captured facial expressions and voice, gathering contextual information about the dynamic audiovisual stimuli is also important. This article discusses recent advances in affect sensing on smartphones and identifies the key barriers and potential solutions for implementing opportunistic and context-aware affect sensing on smartphone platforms. In addition to exploring the technical challenges (privacy, battery life, and robust algorithms), the authors also consider the challenges of recruiting and retaining mental health patients. Experimentation with mental health patients is difficult but crucial to showcase the importance and effectiveness of smartphone-centered affect sensing technology.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Faculty/School / Institute/Centre: Current - Institute for Resilient Regions
Faculty/School / Institute/Centre: Current - Institute for Resilient Regions
Date Deposited: 21 Jun 2016 01:27
Last Modified: 08 Feb 2018 00:01
Uncontrolled Keywords: DSP coprocessor; GPU; healthcare; mental health; mobile; opportunistic affect sensing; pervasive computing; smartphone
Fields of Research (2008): 08 Information and Computing Sciences > 0805 Distributed Computing > 080504 Ubiquitous Computing
Identification Number or DOI: 10.1109/MPRV.2016.36
URI: http://eprints.usq.edu.au/id/eprint/28779

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