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Hybrid Learning Models for IMU-Based HAR with Feature Analysis and Data Correction
This paper proposes a novel approach to tackle the human activity recognition (HAR) problem. Four classes of body movement datasets, namely stand-up, sit-down, run, and walk, are applied to perform HAR. Instead of using vision-based solutions, we address the HAR challenge by implementing a real-time...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537876/ https://www.ncbi.nlm.nih.gov/pubmed/37765863 http://dx.doi.org/10.3390/s23187802 |