Detecção precoce das doenças de Alzheimer e Parkinson através de parâmetros não-lineares multibanda de sinais EEG

Gabriel Silva, Marco Alves, Bruno C. Bispo, Pedro M. Rodrigues

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Abstract

This work aims to detect Alzheimer’s and Parkinson’s diseases at early stage through non-linear multiband para-meters of EEG signals. For each pair of study groups, parameters selection was performed through genetic algorithm. The selected parameters are used as input for classifiers with leave-one-outcross-validation. Classification accuracies of 100% are achieved, in at least one sub band, for 3 pairs of study groups while90.60% is achieved for the Control vs Alzheimer/Parkinson pair. The delta sub band showed, in general, the greatest significant differences between the groups.
Original languagePortuguese
Number of pages5
DOIs
Publication statusPublished - Nov 2020
EventXXXVIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais - Florianópolis, Brazil
Duration: 22 Nov 202025 Nov 2020
https://biblioteca.sbrt.org.br/events/13

Conference

ConferenceXXXVIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
Country/TerritoryBrazil
CityFlorianópolis
Period22/11/2025/11/20
Internet address

Keywords

  • Early detection
  • Alzheimer
  • Parkinson
  • EEG
  • Nonlinear analysis
  • Wavelet

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