Name
Abstract | ||
|---|---|---|
Portable monitoring devices have provided an important cost-effective solution in the development of eHealth applications, providing opportunities for population-wide promotion of physical activity. Monitoring heart profile parameters during extensive activities allows to screen possible pathological conditions, thus helping prevent heart diseses. However, accurately monitoring heart conditions during physical activities represents a challenging problem due to significantly degraded quality of ECG signals. In this paper we propose a solution that enables complete analysis of the ECG signal acquired by a wearable low-cost ECG measuring system, through the implementation of a robust denoising algorithm. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/MeMeA.2018.8438782 | 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA) |
Keywords | Field | DocType |
portable monitoring devices,physical activity,ECG signal,pathological conditions,robust ECG denoising algorithm,e-health applications,heart profile parameter monitoring,heart diseses prevention,heart condition monitoring | Noise reduction,Computer vision,Denoising algorithm,Wearable computer,Computer science,eHealth,Artificial intelligence | Conference |
ISBN | Citations | PageRank |
978-1-5386-3393-9 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandra Galli | 1 | 0 | 1.35 |
| guglielmo frigo | 2 | 55 | 10.64 |
| Giada Giorgi | 3 | 71 | 13.30 |