A Teenager Physical Fitness Evaluation Model Based on 1D-CNN with LSTM and Wearable Running PPG Recordings.

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第一作者： Junqi,Guo

第一单位： School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China.;Engineering Research Center of Intelligent Technology and Educational Application, Ministry of Education, Beijing 100875, China.

作者： Junqi,Guo ^[1] ; Boxin,Wan ^[1] ; Siyu,Zheng ^[2] ; Aohua,Song ^[3] ; Wenshan,Huang ^[3]

作者单位： School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China.;Engineering Research Center of Intelligent Technology and Educational Application, Ministry of Education, Beijing 100875, China. ^[1] School of Electronic Information and Automation, Tianjin University of Science and Technology, Tianjin 300222, China. ^[2] School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China. ^[3]

关键词 Convolutional Neural Network (CNN)Long Short-Term Memory (LSTM)Pearson correlation coefficient (PCC)Photoplethysmography (PPG)deep learning noninvasive biosensors teenager physical fitness monitoring wearable bracelets wireless biosensors

主题词青少年(Adolescent);人工智能(Artificial Intelligence);女(雌)性(Female);人类(Humans);男(雄)性(Male);光体积描记术(Photoplethysmography);身体素质(Physical Fitness);跑(Running)

DOI 10.3390/bios12040202

PMID 35448262

发布时间 2022-07-16

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Biosensors

2022年12卷4期

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A Teenager Physical Fitness Evaluation Model Based on 1D-CNN with LSTM and Wearable Running PPG Recordings.

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A Teenager Physical Fitness Evaluation Model Based on 1D-CNN with LSTM and Wearable Running PPG Recordings.

Biosensors

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