RNN-based deep learning for physical activity recognition using smartwatch sensors: a case study of simple and complex activity recognition

DOI10.3934/MBE.2022265OpenAlexW4226343225MaRDI QIDQ2686722

Sakorn Mekruksavanich, Anuchit Jitpattanakul

Publication date: 28 February 2023

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2022265

zbMATH Keywords

deep learninghuman activity recognitionbidirectional gated recurrent unitcomplex human activitysmartwatch sensors

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Biomechanics (92C10)

Uses Software

• BERT

Cites Work

• BERT
• A daily activity feature extraction approach based on time series of sensor events
• Federated personalized random forest for human activity recognition
• A lightweight double-channel depthwise separable convolutional neural network for multimodal fusion gait recognition
• Intuitionistic fuzzy normed prime and maximal ideals
• Unnamed Item

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