| dc.creator | Bueno-López, Maximiliano | |
| dc.creator | Giraldo, Eduardo | |
| dc.creator | Molinas, Marta | |
| dc.creator | Fosso, Olav Bjarte | |
| dc.date | 2019-01-01T08:00:00Z | |
| dc.date.accessioned | 2022-10-13T13:35:36Z | |
| dc.date.available | 2022-10-13T13:35:36Z | |
| dc.identifier | https://ciencia.lasalle.edu.co/scopus_unisalle/195 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/4157491 | |
| dc.description | This paper presents and discusses the challenge of mode mixing when using the Empirical Mode Decomposition (EMD) to identify intrinsic modes from EEG signals used for neural activity reconstruction. The standard version of the EMD poses some challenges when decomposing signals having intermittency and close spectral proximity in their bands. This is known as the Mode Mixing problem in EMD. Several approaches to solve the issue have been proposed in the literature, but no single technique seems to be universally effective in preserving independent modes after the EMD decomposition. This paper exposes the impact of mode mixing in the process of neural activity reconstruction and reports the results of a performance comparison between a well known strategy, the Ensemble EMD (EEMD), and a new strategy proposed by the authors for mitigating the mode mixing problem. The comparative evaluation shows a more accurate neural reconstruction when employing the strategy proposed by the authors, compared to the use of EEMD and its variants for neural activity reconstruction. | |
| dc.source | IAENG International Journal of Computer Science | |
| dc.source | 1 | |
| dc.subject | EEG signals | |
| dc.subject | Empirical Mode Decomposition | |
| dc.subject | Mode Mixing | |
| dc.title | The mode mixing problem and its influence in the neural activity reconstruction | |
| dc.type | Article | |
