Pablo Paredes

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2016-37

May 1, 2016

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-37.pdf

Abstract Pervasive Well-being Technology by Pablo Enrique Paredes Castro Doctor of Philosophy in Computer Science University of California, Berkeley Professor John F. Canny, Chair

Well-being is the characteristic of humans to feel well with themselves and their environment. A key driver of wellbeing is to have a healthy mind. Stress management, positive emotions, and empathic social interaction get us closer to this goal. The only sustainable way towards wellbeing is by maintaining a healthy lifestyle. In summary, technologies supporting this objective should measure and intervene "life" itself!

The good news is that we are in a unique position to challenge the way technology can become a driver of wellbeing. Internet of things (IoT), Big Data, Affective Computing and Critical Engineering, are the key enablers. With pervasive data, interventions can evolve from being reactive to predictive. We could design long-term interventions that foster good habits, resilience, and personal growth. We encapsulate technologies in two parts: "Conceptualization and Sensor-less Sensing" and "Opportunistic Interventions." The former uses data streams to investigate and measure human traits and trends. The latter repurposes popular apps, devices, and environments into effective interventions. 

In summary, we aim at designing well-being technology that could survive the chasm of adoption and attrition.

Advisors: John F. Canny

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BibTeX citation:

@phdthesis{Paredes:EECS-2016-37,
    Author= {Paredes, Pablo},
    Title= {Pervasive Well-being Technology},
    School= {EECS Department, University of California, Berkeley},
    Year= {2016},
    Month= {May},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-37.html},
    Number= {UCB/EECS-2016-37},
    Abstract= {Abstract
Pervasive Well-being Technology
by
Pablo Enrique Paredes Castro
Doctor of Philosophy in Computer Science
University of California, Berkeley
Professor John F. Canny, Chair

Well-being is the characteristic of humans to feel well with themselves and their environment. A key driver of wellbeing is to have a healthy mind. Stress management, positive emotions, and empathic social interaction get us closer to this goal. The only sustainable way towards wellbeing is by maintaining a healthy lifestyle. In summary, technologies supporting this objective should measure and intervene "life" itself!

The good news is that we are in a unique position to challenge the way technology can become a driver of wellbeing. Internet of things (IoT), Big Data, Affective Computing and Critical Engineering, are the key enablers. With pervasive data, interventions can evolve from being reactive to predictive. We could design long-term interventions that foster good habits, resilience, and personal growth. We encapsulate technologies in two parts: "Conceptualization and Sensor-less Sensing" and "Opportunistic Interventions." The former uses data streams to investigate and measure human traits and trends. The latter repurposes popular apps, devices, and environments into effective interventions. 

In summary, we aim at designing well-being technology that could survive the chasm of adoption and attrition.},
}

EndNote citation:

%0 Thesis
%A Paredes, Pablo 
%T Pervasive Well-being Technology
%I EECS Department, University of California, Berkeley
%D 2016
%8 May 1
%@ UCB/EECS-2016-37
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-37.html
%F Paredes:EECS-2016-37