Using a Hybrid Neural Network and a Regularized Extreme Learning Machine for Human Activity Recognition with Smartphone and Smartwatch.

Tan, Tan-Hsu; Shih, Jyun-Yu; Liu, Shing-Hong; Alkhaleefah, Mohammad; Chang, Yang-Lang; Gochoo, Munkhjargal

Tan, Tan-Hsu; Shih, Jyun-Yu; Liu, Shing-Hong; Alkhaleefah, Mohammad; Chang, Yang-Lang; Gochoo, Munkhjargal.

Afiliação

Tan TH; Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan.
Shih JY; Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan.
Liu SH; Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung 413310, Taiwan.
Alkhaleefah M; Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan.
Chang YL; Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan.
Gochoo M; Department of Computer Science and Software Engineering, United Arab Emirates University, Al-Ain 15551, United Arab Emirates.

Sensors (Basel) ; 23(6)2023 Mar 22.

Article em En | MEDLINE | ID: mdl-36992065

Assuntos

Redes Neurais de Computação; Smartphone; Humanos; Idoso; Algoritmos; Aprendizado de Máquina; Atividades Humanas

Palavras-chave

bidirectional gated recurrent unit (BiGRU); human activity recognition; mHealth; regularized extreme machine learning (RELM)

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Smartphone Tipo de estudo: Prognostic_studies Limite: Aged / Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article

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