Name
Abstract | ||
|---|---|---|
In many biomedical measurement procedures, it is important to record a huge amount of data, to monitor the state of health of a subject. In such a context, electroencephalograph (EEG) data are one of the most demanding in terms of size and signal behavior. In this paper, we propose a near-lossless compression algorithm for EEG signals able to achieve a compression ratio in the order of 10 with a r... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MeMeA52024.2021.9478756 | 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA) |
Keywords | DocType | ISBN |
Noise reduction,Memory management,Signal processing algorithms,Tools,Distortion,Electroencephalography,Distortion measurement | Conference | 978-1-6654-1914-7 |
Citations | PageRank | References |
2 | 0.42 | 0 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giuseppe Campobello | 1 | 2 | 0.76 |
| Angelica Quercia | 2 | 2 | 0.42 |
| Giovanni Gugliandolo | 3 | 2 | 0.76 |
| Antonino Segreto | 4 | 2 | 0.42 |
| Elisa Tatti | 5 | 2 | 0.76 |
| Maria Felice Ghilardi | 6 | 2 | 0.76 |
| Giovanni Crupi | 7 | 2 | 0.76 |
| Angelo Quartarone | 8 | 2 | 0.76 |
| Nicola Donato | 9 | 2 | 0.76 |