Name
Abstract | ||
|---|---|---|
The authors present an approach for designing self-monitoring technology called "semi-automated tracking," which combines both manual and automated data collection methods. Through this approach, they aim to lower the capture burdens, collect data that is typically hard to track automatically, and promote awareness to help people achieve their self-monitoring goals. They first specify three design considerations for semi-automated tracking: data capture feasibility, the purpose of self-monitoring, and the motivation level. They then provide examples of semi-automated tracking applications in the domains of sleep, mood, and food tracking to demonstrate strategies they developed to find the right balance between manual tracking and automated tracking, combining each of their benefits while minimizing their associated limitations. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/MPRV.2017.18 | IEEE Pervasive Computing |
Keywords | Field | DocType |
Monitoring,Sensors,Insulation life,Data collection,Mood tracking,Pervasive computing,Medical devices,Internet of things,Informatics | Personal informatics,Data collection,Computer science,Internet of Things,Human–computer interaction,Automatic identification and data capture,Ubiquitous computing,Self-monitoring,Group method of data handling | Journal |
Volume | Issue | ISSN |
16 | 1 | 1536-1268 |
Citations | PageRank | References |
17 | 0.65 | 16 |
Authors | ||
13 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eun Kyoung Choe | 1 | 518 | 38.00 |
| Saeed Abdullah | 2 | 198 | 18.46 |
| Mashfiqui Rabbi | 3 | 303 | 20.59 |
| Edison Thomaz | 4 | 245 | 17.29 |
| Daniel A. Epstein | 5 | 308 | 21.56 |
| Felicia Cordeiro | 6 | 111 | 5.57 |
| Matthew Kay | 7 | 451 | 30.42 |
| Gregory D. Abowd | 8 | 11979 | 1503.13 |
| Tanzeem Choudhury | 9 | 4137 | 306.53 |
| James Fogarty | 10 | 2343 | 164.17 |
| Bongshin Lee | 11 | 2738 | 143.95 |
| Mark Matthews | 12 | 167 | 14.74 |
| Julie Kientz | 13 | 1796 | 141.34 |