Cargando…
Automatic Classification of Squat Posture Using Inertial Sensors: Deep Learning Approach
Without expert coaching, inexperienced exercisers performing core exercises, such as squats, are subject to an increased risk of spinal or knee injuries. Although it is theoretically possible to measure the kinematics of body segments and classify exercise forms with wearable sensors and algorithms,...
Autores principales: | Lee, Jaehyun, Joo, Hyosung, Lee, Junglyeon, Chee, Youngjoon |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014149/ https://www.ncbi.nlm.nih.gov/pubmed/31936407 http://dx.doi.org/10.3390/s20020361 |
Ejemplares similares
-
Porcine lie detectors: Automatic quantification of posture state and transitions in sows using inertial sensors
por: Thompson, Robin, et al.
Publicado: (2016) -
Training Data Selection and Optimal Sensor Placement for Deep-Learning-Based Sparse Inertial Sensor Human Posture Reconstruction
por: Zheng, Zhaolong, et al.
Publicado: (2021) -
Measuring postural stability with an inertial sensor: validity and sensitivity
por: Neville, Christopher, et al.
Publicado: (2015) -
Gait Activity Classification on Unbalanced Data from Inertial Sensors Using Shallow and Deep Learning
por: Lopez-Nava, Irvin Hussein, et al.
Publicado: (2020) -
Wearable Sensor Based Stooped Posture Estimation in Simulated Parkinson’s Disease Gaits
por: Dang, Quoc Khanh, et al.
Publicado: (2019)