The impact of synthetic data on fall detection application
Lack of real-world data in clinical fields poses a major obstacle for training deep learning
models. Using data augmentation can increase data volume, making the training of deep …
models. Using data augmentation can increase data volume, making the training of deep …
Fall Prediction by a Spatio-Temporal Multi-Channel Causal Model from Wearable Sensors Data
G Liao, J Liu, Y Liang, S Wang… - ICASSP 2024-2024 IEEE …, 2024 - ieeexplore.ieee.org
Predicting human falls from wearable devices is a complex task due to the inherent diversity
and causality of multivariate physical changes, where each instance exhibits a unique style …
and causality of multivariate physical changes, where each instance exhibits a unique style …
Um método para monitoramento e geração de feedbacks em atividades físicas repetitivas baseado em Máquinas de Boltzmann Restritas
MAC Alencar - 2023 - tede.ufam.edu.br
A prática de atividades físicas, muitas vezes realizadas em ambientes como academias e
sessões de fisioterapia, exige a execução precisa dos movimentos para garantir resultados …
sessões de fisioterapia, exige a execução precisa dos movimentos para garantir resultados …
A robust fall detection approach based on 4D imaging millimeter-wave radar
J Xiao, Z Yang, P Chu, J Zhou - … International Conference on …, 2024 - spiedigitallibrary.org
Falls are the leading cause of injuries and even fatalities among elderly individuals in home
environments, resulting in the development of fall detection technology particularly crucial. In …
environments, resulting in the development of fall detection technology particularly crucial. In …