Impact of sampling rate and eye-condition on resting quantitative EEG (2022)
- Authors:
- USP affiliated authors: ROSA, JOÃO LUIS GARCIA - ICMC ; AGUIAR NETO, FERNANDO SOARES DE - ICMC
- Unidade: ICMC
- DOI: 10.23919/SPA53010.2022.9927794
- Subjects: PROCESSAMENTO DE SINAIS BIOMÉDICOS; INFERÊNCIA BAYESIANA; AMOSTRAGEM; ELETROENCEFALOGRAFIA
- Keywords: qEEG; EEG; healthy; RDoC
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- Conference titles: Signal Processing Conference - SPA
- Status:
- Nenhuma versão em acesso aberto identificada
-
ABNT
AGUIAR NETO, Fernando Soares de e ROSA, João Luís Garcia. Impact of sampling rate and eye-condition on resting quantitative EEG. 2022, Anais.. Poznan: IEEE, 2022. Disponível em: https://doi.org/10.23919/SPA53010.2022.9927794. Acesso em: 29 mar. 2026. -
APA
Aguiar Neto, F. S. de, & Rosa, J. L. G. (2022). Impact of sampling rate and eye-condition on resting quantitative EEG. In Proceedings. Poznan: IEEE. doi:10.23919/SPA53010.2022.9927794 -
NLM
Aguiar Neto FS de, Rosa JLG. Impact of sampling rate and eye-condition on resting quantitative EEG [Internet]. Proceedings. 2022 ;[citado 2026 mar. 29 ] Available from: https://doi.org/10.23919/SPA53010.2022.9927794 -
Vancouver
Aguiar Neto FS de, Rosa JLG. Impact of sampling rate and eye-condition on resting quantitative EEG [Internet]. Proceedings. 2022 ;[citado 2026 mar. 29 ] Available from: https://doi.org/10.23919/SPA53010.2022.9927794 - Depression biomarkers using non-invasive EEG: a review
- Early detection of autism spectrum disorder using non-invasive EEG
- Pre-processing approaches for collaborative filtering based on hierarchical clustering
- Artificial neural networks: models and applications
- A hybrid symbolic-connectionist processor of natural language semantic relations
- Biologically plausible artificial neural networks
- An architecture for semantic role labeling on portuguese
- Metaphone-pt_BR: the phonetic importance on search and correction of textual information
- How an epileptic EEG segment, used as reference, can influence a cross-correlation classifier?
- The use of one-class classifiers for differentiating healthy from epileptic EEG segments
Informações sobre a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3105565.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
