The Quantified Self on Location

Instructor: Arlene Ducao,
Office Hours: Thursdays by appointment.

Dates: Alternating Thursdays starting January 30 (seven sessions)
Time: 3:30-6 PM
Room: 50


As our devices have shrunk in size and grown in computational capacity, we’ve seen an explosion of technology meant to enhance our lives through bio-metric and geo-located data. Anticipation around the combination of these data is high, especially as companies like Apple and Google start developing wearable hardware. In this class, we’ll prototype devices that combine bio-sensors and GPS, and we’ll examine the implications of aggregating and analyzing this data for the individual, the community, the city, and beyond.


This class will be a series of design sessions, though technical and theoretical issues will be covered as well. This proportion is flexible based on student interest and experience.


Due dates are hard dates.

Bi-weekly blog posts based on class discussions, readings, and tinkering. Blog posts are due before each class. All students must blog as individuals. Comments on other student posts are encouraged, particularly as a reflection of student interaction.

Midterm, due March 27: a concept poster and partial implementation of a practical, creative device that implements geolocation and biological data. Teams of at least two people are encouraged for the midterm.

Final, due April 24: a refinement and full implementation of the proposed prototype. Teams of at least two people are encouraged for the final.

Recommended Prerequisites

Students should familiarize themselves with C, Arduino, HTML5, Javascript, a map library like Leaflet, and GPS syntax. Deep proficiency is not required, but be prepared to work with these tools.

Recommended hardware: an Arduino Uno, an Adafruit Ultimate GPS Data Logger Shield, a microSD card, and a bio-metric sensor that can interface with these devices.

General Class Structure

  • 45 minutes: discussion on pre-class topics, i.e. intros, assignments, reading, observations from world, etc.
  • 45 minutes: new material
  • 10 minute break
  • 30 minutes: integration of new material, preparing for the next two weeks
  • 20 minutes: final Q&A

Class Schedule [REVISED due to SNOW]

  • January 30: Intro/overview. Discussion of student needs. Academic (Physiological Computing Interface) literature review.
  • February 27: Workshop: Bio-sensors, GPS.
  • March 13: Workshop: Spatial visualization. Midterm proposals from teams.
  • March 27: Midterm presentations.
  • April 3: Workshop: structuring user studies. Commercial and art literature review.
  • April 10: Final proposals from teams. Discussion and tech troubleshooting.
  • April 24: Final Presentations (possible guest critics).


  • Class Participation: 40%
  • Weekly Assignments: 15%
  • Midterm Project: 15%
  • Final Project: 30%


Class is short, so come on time.
Lateness (more than 5 minutes) or early departure from class translates into one half absence.
Two unexcused absences will result in an academic warning.
Four absences are grounds for failure.

Do not use e-devices for tasks unrelated to class. The quality of class depends on all of our attention and active participation, so please respect.

Unexcused absences on project due dates will constitute a failure of that assignment. If you have an excused absence, you will have to arrange for an out-of-class appointment to review your work. If you are part of a team, your work will be critiqued on the assignment due date by the member who is present.

In exceptional cases, at the discretion of the professor, a student may be excused from class.  Leave will be considered 1 week (or more) before the class in question but not after that time.  This does not apply to sudden illness, a death in the family, or other last-minute exigencies.  Situations, which merit consideration for leave from a class, include:
-Unique and compelling professional opportunities relevant to your studies
-Important family events (weddings, funerals, and the like)
-Incapacitating or contagious illness  (NB: A student must call or e-mail the professor BEFORE the class time if he or she cannot attend as a result of serious illness.  Failure to do so will result in an unexcused absence.)
-Religious holidays

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