Abstract
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 language | English |
|---|---|
| Title of host publication | CHI 2017 Extended Abstracts - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems |
| Subtitle of host publication | Explore, Innovate, Inspire |
| Pages | 510-517 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781450346566 |
| DOIs | |
| State | Published - 6 May 2017 |
| Event | 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 - Denver, United States Duration: 6 May 2017 → 11 May 2017 |
Publication series
| Name | Conference on Human Factors in Computing Systems - Proceedings |
|---|---|
| Volume | Part F127655 |
Conference
| Conference | 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 |
|---|---|
| Country/Territory | United States |
| City | Denver |
| Period | 6/05/17 → 11/05/17 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Citizen science
- Digital health
- Quantified self
- Self-experimentation
- Self-tracking
All Science Journal Classification (ASJC) codes
- Software
- Human-Computer Interaction
- Computer Graphics and Computer-Aided Design
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