Name
Abstract | ||
|---|---|---|
Changes in daily habits can provide important information regarding the overall health status of an individual. This research aimed to determine how meaningful information may be extracted from limited sensor data and transformed to provide clear visualization for the clinicians who must use and interact with the data and make judgments on the condition of patients. We ascertained that a number of insightful features related to habits and physical condition could be determined from usage and motion sensor data. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1186/s12911-014-0102-x | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
habits,motion,qualitative research,feature extraction,visualization,health informatics,user centered design,medical informatics | Telemedicine,Data mining,CLARITY,Clinical decision making,Computer science,Visualization,Feature extraction,Human–computer interaction,Health informatics,Qualitative research,User-centered design | Journal |
Volume | Issue | ISSN |
14 | 1 | 1472-6947 |
Citations | PageRank | References |
2 | 0.45 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joost De Folter | 1 | 3 | 1.13 |
| Hulya Gokalp | 2 | 2 | 1.46 |
| Joanna Fursse | 3 | 16 | 2.06 |
| Urvashi Sharma | 4 | 3 | 0.83 |
| malcolm clarke | 5 | 42 | 7.66 |