D1NAMO, A Personal Health System for Glycemic Events Detection
| Tipo de publicação: | Inproceedings |
| Citação: | |
| Booktitle: | Workshop Artificial Intelligence for Diabetes, 22nd European Conference on Artificial Intelligence (ECAI 2016) |
| Ano: | 2016 |
| Mês: | August |
| Location: | The Hague, Netherlands |
| Organização: | ECAI |
| Resumo: | 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. |
| Palavras-chave: | |
| Autores | |
| Adicionado por: | [] |
| Total mark: | 0 |
|
Anexos
|
|
|
|
|
Notas
|
|
|
|
|
|
Tópicos
|
|
|
|
|
