Cargando…
Sensor Data Acquisition and Multimodal Sensor Fusion for Human Activity Recognition Using Deep Learning
In this paper, we perform a systematic study about the on-body sensor positioning and data acquisition details for Human Activity Recognition (HAR) systems. We build a testbed that consists of eight body-worn Inertial Measurement Units (IMU) sensors and an Android mobile device for activity data col...
Autores principales: | Chung, Seungeun, Lim, Jiyoun, Noh, Kyoung Ju, Kim, Gague, Jeong, Hyuntae |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479605/ https://www.ncbi.nlm.nih.gov/pubmed/30974845 http://dx.doi.org/10.3390/s19071716 |
Ejemplares similares
-
Multi-Path and Group-Loss-Based Network for Speech Emotion Recognition in Multi-Domain Datasets
por: Noh, Kyoung Ju, et al.
Publicado: (2021) -
Novel Deep Learning Network for Gait Recognition Using Multimodal Inertial Sensors
por: Shi, Ling-Feng, et al.
Publicado: (2023) -
Multimodal Sensor-Input Architecture with Deep Learning for Audio-Visual Speech Recognition in Wild
por: He, Yibo, et al.
Publicado: (2023) -
Deep Learning for Sensor-Based Rehabilitation Exercise Recognition and Evaluation†
por: Zhu, Zheng-An, et al.
Publicado: (2019) -
Deep Learning–Based Multimodal Data Fusion: Case Study in Food Intake Episodes Detection Using Wearable Sensors
por: Bahador, Nooshin, et al.
Publicado: (2021)