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The Truth behind Quantified self


Deze informatie is alleen in het Engels beschikbaar.
UPDATE 18-09-2023: Start of the class moved by one week.

Topics: Real world data, digital health, data interpretation, new technologies, complex systems.
Disciplines: Psychology, Neuroscience, Physiology, Data Science, Engineering, Systems Sciences.
Skills: Researching, Project-based working, Collaborating, Oral communication, Written communication, Presenting, Reflecting, Independent learning

Admission requirements:

This course is an (extracurricular) Honours Class: an elective course within the Honours College programme. Third year students who don’t participate in the Honours College, have the opportunity to apply for a Bachelor Honours Class. Students will be selected based on i.a. their motivation and average grade.


Our mood states, caloric intake, physical activity and even our skin conductance; in our modern digital society it is possible to track every single bit of our daily lives with various types of tracking devices. Using this data, our health and personal development can be analysed and modified to improve our functioning. It leads to a self expressed in numbers, a so-called “quantified self”.

This course will enable students to critically examine the current developments in the digital-data industry and separate the truth from the hype of these developments. In this course, students will examine the claims of the information revolution with a focus on the quantified self – for instance driven by wearables or Facebook usage. Students will survey the ongoing developments in this area based on news reports and peer-reviewed literature. Through brief written reports and in-class presentations, students will reveal their findings in terms of scientific validity and societal implications. For each seminar, students will choose a technology and will connect with the guiding theme of the seminar.

The chosen technology (current or futuristic but realistic) may be for instance:

  • Social network data;

  • Global positioning;

  • Accelerometry;

  • Portable EEG.

The guiding themes to connect with may include:

  • Data mining on rich vs. poor;

  • The perception of privacy;

  • Scientific validation of claims;

  • Data in diseases.

Course objectives:

Upon successful completion of this course, students will:

  • Gain a comprehensive survey of the possible technologies used towards quantifying human behaviour in the real world;

  • Get exposure to data from the real world in terms of measurement noise, transformation to metrics, and the path to scientific validity in its usage in improving human health;

  • Identify and articulate the advantages of each data channel and the corresponding societal impact;

  • Evaluate scientific reports on the use of digital data in the well-being and health industry.

Programme and timetable:

The sessions of this class will take place on the following Wednesdays 19.30 - 21.30:

Session 1: October 4
Introduction to the course & match making

Session 2: October 25
Hardware description

Session 3: November 1
History of the sensor

Session 4: November 22
From data to metrics

Session 5: November 29
The impact on health

Session 6: December 6
Social and economic impact

Session 7: December 20

Pieter de la Court building, room 1B01 (Living Lab)

Reading list:

  • The patient will see you now. Eric Topol (Optional);

  • Self-Tracking. Gina Neff & Dawn Nafus (Optional);

  • Current articles from peer-reviewed literature (Mandatory).

Peer-reviewed literature will be announced in class or via Brightspace.

Course load and teaching method:

This course is worth 5 ECTS, which means the total course load equals 140 hours.

  • Seminars: 7 seminars of 2,5 hours (participation is mandatory);

  • Seminar preparation, literature reading and assignments: 17,5 hours per seminar.

Assessment methods:

The assessment methods will look as follows (will be further explained in the first session of the class):

  • 70% seminar presentations;

  • 20% short reports (150 words per seminar);

  • 10% in-class participation continuously evaluated.

Students can only pass this course after successful completion of all partial exams.

Please note: Attendance is compulsory.

Students can only pass this course after successful completion of all partial exams.

Brightspace and uSis:

Brightspace will be used in this course. Upon admission students will be enrolled in Brightspace by the teaching administration.

Please note: students are not required to register through uSis for the Bachelor Honours Classes. Your registration will be done centrally.

Application process:

Submitting an application for this course is possible from Monday 21 August 2023 up to and including Tuesday 12 September 2023 23:59 through the link on the Honours Academy student website.

Note: students don’t have to register for the Bachelor Honours Classes in uSis. The registration is done centrally before the start of the class.

Dr. Arko Ghosh: