NE-Motion: visual analysis of stroke patients using motion sensor networks (2021)
- Authors:
- USP affiliated authors: NONATO, LUIS GUSTAVO - ICMC ; CONTRERAS, RODRIGO COLNAGO - ICMC
- Unidade: ICMC
- DOI: 10.3390/s21134482
- Subjects: TEORIA DOS CONJUNTOS; VISUALIZAÇÃO; ACIDENTE VASCULAR CEREBRAL
- Keywords: visual analytics; graph learning; stroke
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
ABNT
CONTRERAS, Rodrigo Colnago et al. NE-Motion: visual analysis of stroke patients using motion sensor networks. Sensors, v. 21, p. 1-22, 2021Tradução . . Disponível em: https://doi.org/10.3390/s21134482. Acesso em: 27 dez. 2025. -
APA
Contreras, R. C., Parnandi, A., Coelho, B. G., Silva, C., Schambra, H., & Nonato, L. G. (2021). NE-Motion: visual analysis of stroke patients using motion sensor networks. Sensors, 21, 1-22. doi:10.3390/s21134482 -
NLM
Contreras RC, Parnandi A, Coelho BG, Silva C, Schambra H, Nonato LG. NE-Motion: visual analysis of stroke patients using motion sensor networks [Internet]. Sensors. 2021 ; 21 1-22.[citado 2025 dez. 27 ] Available from: https://doi.org/10.3390/s21134482 -
Vancouver
Contreras RC, Parnandi A, Coelho BG, Silva C, Schambra H, Nonato LG. NE-Motion: visual analysis of stroke patients using motion sensor networks [Internet]. Sensors. 2021 ; 21 1-22.[citado 2025 dez. 27 ] Available from: https://doi.org/10.3390/s21134482 - A new multi-filter framework with statistical dense SIFT descriptor for spoofing detection in fingerprint authentication systems
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Informações sobre o DOI: 10.3390/s21134482 (Fonte: oaDOI API)
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