Development of a multi-wear-site, deep learning-based physical activity intensity classification algorithm using raw acceleration data

JYY Ng, JH Zhang, SS Hui, G Jiang, F Yau, J Cheng… - Plos one, 2024 - journals.plos.org
Background Accelerometers are widely adopted in research and consumer devices as a tool
to measure physical activity. However, existing algorithms used to estimate activity intensity …

Detection of human fall using floor vibration and multi-features semi-supervised SVM

C Liu, Z Jiang, X Su, S Benzoni, A Maxwell - Sensors, 2019 - mdpi.com
Human falls are the premier cause of fatal and nonfatal injuries among older adults. The
health outcome of a fall event is largely dependent on rapid response and rescue of the …

[HTML][HTML] On the feature extraction process in machine learning. An experimental study about guided versus non-guided process in falling detection systems

E Escobar-Linero, F Luna-Perejón… - … Applications of Artificial …, 2022 - Elsevier
Falls are current events that can lead to severe injuries and even accidental deaths among
the population, especially the elderly. Since them usually live alone and their contact with …

Evaluating pose estimation as a solution to the fall detection problem

YR Serpa, MB Nogueira, PPM Neto… - 2020 IEEE 8th …, 2020 - ieeexplore.ieee.org
In this age of evolving technological capabilities, assisted living has proven useful to ease
the frailty that comes with aging. Within this context, the detection and prevention of …

Deep learning-based fall detection algorithm using ensemble model of coarse-fine CNN and GRU networks

CP Liu, JH Li, EP Chu, CY Hsieh, KC Liu… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
Falls are the public health issue for the elderly all over the world since the fall-induced
injuries are associated with a large amount of healthcare cost. Falls can cause serious …

A review of IoT architectures in smart healthcare applications

M Arbaoui, A Rahmoun - 2022 Seventh International …, 2022 - ieeexplore.ieee.org
The Internet of Things (IoT) is revolutionizing numerous industries, including healthcare
services, known as the Internet of Medical Things (IoMT). A large amount of generated data …

CMFALL: A cascade and parallel multi-state fall detection algorithm using waist-mounted tri-axial accelerometer signals

G Wang, Q Li, L Wang, Y Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
As one of the main threats to people's health, especially for the elderly, falls have caused a
large number of accidents. Detecting falls in time can minimize the severity of the injury and …

Deep learning in pervasive health monitoring, design goals, applications, and architectures: An overview and a brief synthesis

A Boulemtafes, H Khemissa, MS Derki, A Amira… - Smart Health, 2021 - Elsevier
The continuous growth of an aging population in some countries, and patients with chronic
conditions needs the development of efficient solutions for healthcare. Pervasive Health …

[HTML][HTML] Rich learning representations for human activity recognition: How to empower deep feature learning for biological time series

R Kanjilal, I Uysal - Journal of Biomedical Informatics, 2022 - Elsevier
Deep learning versus feature engineering has drawn significant attention specifically for
applications where expertly crafted features have been used for decades. Human activity …

Ultra-wideband data as input of a combined EfficientNet and LSTM architecture for human activity recognition

A Beaulieu, F Thullier, K Bouchard… - Journal of Ambient …, 2022 - content.iospress.com
The world population is aging in the last few years and this trend is expected to increase in
the future. The number of persons requiring assistance in their everyday life is also expected …