Artificial Intelligence Based Approach for Classification of Human Activities Using MEMS Sensors Data.

Khan, Yusuf Ahmed; Imaduddin, Syed; Singh, Yash Pratap; Wajid, Mohd; Usman, Mohammed; Abbas, Mohamed

Khan, Yusuf Ahmed; Imaduddin, Syed; Singh, Yash Pratap; Wajid, Mohd; Usman, Mohammed; Abbas, Mohamed.

Afiliação

Khan YA; Department of Electronics Engineering, ZHCET, Aligarh Muslim University, Aligarh 202002, India.
Imaduddin S; Department of Electronics Engineering, ZHCET, Aligarh Muslim University, Aligarh 202002, India.
Singh YP; Department of Electronics Engineering, ZHCET, Aligarh Muslim University, Aligarh 202002, India.
Wajid M; Department of Electronics Engineering, ZHCET, Aligarh Muslim University, Aligarh 202002, India.
Usman M; Department of Electrical Engineering, King Khalid University, Abha 61411, Saudi Arabia.
Abbas M; Electrical Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia.

Sensors (Basel) ; 23(3)2023 Jan 22.

Article em En | MEDLINE | ID: mdl-36772315

Assuntos

Sistemas Microeletromecânicos; Dispositivos Eletrônicos Vestíveis; Humanos; Inteligência Artificial; Teorema de Bayes; Atividades Humanas

Palavras-chave

Bi-LSTM network; MEMS sensors; classification algorithm; deep learning; deep neural network; human activity recognition; machine learning; mobile & wearable devices; recurrent neural network

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas Microeletromecânicos / Dispositivos Eletrônicos Vestíveis Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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