Digital health & self-experimentation: Design challenges & provocations

Markéta Dolejšová, Denisa Kera, Cristiano Storni, Rohit Ashok Khot, Ivan John Clement, Inka Pavelka, Puneet Kishor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations


Quantified self-experimentation with personal health is a growing activity among health enthusiasts, biohackers, and patients with chronic conditions. By collecting and sharing their health data through self-tracking devices and health networking services, self-experimenters engage in a unique form of n=1 citizen science-style research. This data sharing altruism is constrained by limited data security, validity, and socioeconomic access. We will explore these issues as design challenges. The workshop invites various stakeholders (private, corporate, non-profit, academic) to engage in a discussion and a performative prototyping of a design framework for transparent and just health self-experimentation.

Original languageEnglish
Title of host publicationCHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publicationExplore, Innovate, Inspire
PublisherAssociation for Computing Machinery
Number of pages8
ISBN (Electronic)9781450346566
StatePublished - 6 May 2017
Externally publishedYes
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 - Denver, United States
Duration: 6 May 201711 May 2017

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
VolumePart F127655


Conference2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
Copyright © 2017 by the Association for Computing Machinery, Inc. (ACM).


  • Citizen science
  • Digital health
  • Quantified self
  • Self-experimentation
  • Self-tracking


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