D1NAMO, A Personal Health System for Glycemic Events Detection
| Art der Publikation: | Artikel in einem Konferenzbericht |
| Zitat: | |
| Buchtitel: | Workshop Artificial Intelligence for Diabetes, 22nd European Conference on Artificial Intelligence (ECAI 2016) |
| Jahr: | 2016 |
| Monat: | August |
| Ort: | The Hague, Netherlands |
| Organisation: | ECAI |
| Abriss: | Several approaches are used nowadays to help diabetic people to handle their disease, one of them being the self-management of diabetes. We developed in this context a platform allowing patients to report and log their symptoms,medications and glucose levels through an Android application. In addition to self-management, the \DINAMO{} project aims at using ECG signals in order to detect glycemic events and eventually predict glycemia levels. The BioHarness Zephyr 3 sensor has been integrated in the platform for this purpose. The resulting platform is a full-stack personal health system for diabetes self-management with support for physiological signals such as ECG: a physiological signals sensor, an Android application, a central server, a database and a few webpages are composing it. The question of the data lifecycle management in regards to the platform usages is discussed. |
| Schlagworte: | |
| Autoren | |
| Hinzugefügt von: | [] |
| Gesamtbewertung: | 0 |
|
Anhänge
|
|
|
|
|
Notizen
|
|
|
|
|
|
Themen
|
|
|
|
