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Classification of Electroencephalogram Signal for Developing Brain-Computer Interface Using Bioinspired Machine Learning Approach.
Thilagaraj, M; Ramkumar, S; Arunkumar, N; Durgadevi, A; Karthikeyan, K; Hariharasitaraman, S; Rajasekaran, M Pallikonda; Govindan, Petchinathan.
Afiliação
  • Thilagaraj M; Department of Electronics and Instrumentation Engineering, Karpagam College of Engineering, Coimbatore, India.
  • Ramkumar S; School of Computing, Kalasalingam Academy of Research and Education, Virudhunagar, India.
  • Arunkumar N; Department of Biomedical Engineering, Rathinam Technical Campus, Coimbatore, India.
  • Durgadevi A; Department of Electrical and Electronics Engineering, K. Ramakrishnan College of Engineering, Trichy, India.
  • Karthikeyan K; Department of Electrical and Electronics Engineering, Ramco Institute of Technology, Rajapalayam, India.
  • Hariharasitaraman S; School of Computer Science and Engineering, VIT Bhopal, Bhopal, Madhya Pradesh, India.
  • Rajasekaran MP; Department of Electronics and Communication Engineering, Kalasalingam Academy of Research and Education, Virudhunagar, India.
  • Govindan P; Department of Electrical and Electronics Technology, Ethiopian Technical University, Addis Ababa, Ethiopia.
Comput Intell Neurosci ; 2022: 4487254, 2022.
Article em En | MEDLINE | ID: mdl-35251147
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Eletroencefalografia / Interfaces Cérebro-Computador / Aprendizado de Máquina Tipo de estudo: Prognostic_studies Limite: Adult / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Eletroencefalografia / Interfaces Cérebro-Computador / Aprendizado de Máquina Tipo de estudo: Prognostic_studies Limite: Adult / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article