Abstract
A growing number of studies use wearable sensors, including cameras, to detect user activity patterns. When an object of academic investigation, these patterns are interpreted by researchers and conclusions are drawn about people's habits and routines. Alternatively, interpretations are provided by users themselves during extensive post-study interviews. Such approaches inevitably expose personal data collected about individuals to researchers, which can potentially change the behavior under investigation. We introduce a new approach to using wearable sensor data in research. It allows people to interpret and selfreflect on their data and submit for investigation only reflections, without sharing their raw data. In this interactivity, we present and discuss the Datawear mobile application prototype, which is designed to conduct "in the wild" studies of personal experiences.
Original language | English |
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Title of host publication | CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems |
Subtitle of host publication | Crossings |
Publisher | ACM |
Pages | 323-326 |
Number of pages | 4 |
ISBN (Electronic) | 9781450331463 |
DOIs | |
Publication status | Published - 18 Apr 2015 |
Event | 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 - Seoul, Korea, Republic of Duration: 18 Apr 2015 → 23 Apr 2015 |
Publication series
Name | Conference on Human Factors in Computing Systems - Proceedings |
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Volume | 18 |
Conference
Conference | 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 18/04/15 → 23/04/15 |
Bibliographical note
Funding Information:The study is supported by Horizon Digital Economy Research (Research Councils UK grant EP/G065802/1).
Keywords
- Ethics
- Experience sampling
- Self-reflection
- Sensors
- Wearable cameras