Fall detection systems for internet of medical things based on wearable sensors: A review

Z Jiang, MAA Al-Qaness, ALA Dalal… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Fall detection (FD) systems are crucial for identifying falls and ensuring timely assistance,
thus reducing the risk of serious injuries. With the development of society and increasing …

Human activity recognition using binary sensors: A systematic review

MTR Khan, E Ever, S Eraslan, Y Yesilada - Information Fusion, 2024 - Elsevier
Human activity recognition (HAR) is an emerging area of study and research field that
explores the development of automated systems to identify and categorize human activities …

TCN-inception: temporal convolutional network and inception modules for sensor-based human activity recognition

MAA Al-qaness, A Dahou, NT Trouba… - Future Generation …, 2024 - Elsevier
Abstract The field of Human Activity Recognition (HAR) has experienced a significant surge
in interest due to its essential role across numerous areas, including human–computer …

Human activity recognition and fall detection using convolutional neural network and transformer-based architecture

MAA Al-qaness, A Dahou, M Abd Elaziz… - … Signal Processing and …, 2024 - Elsevier
Abstract Human Activity Recognition (HAR) and fall detection, as applications within the field
of biomedical signal processing, are increasingly pivotal in enhancing patient care …

[HTML][HTML] Deep wavelet convolutional neural networks for multimodal human activity recognition using wearable inertial sensors

TH Vuong, T Doan, A Takasu - Sensors, 2023 - mdpi.com
Recent advances in wearable systems have made inertial sensors, such as accelerometers
and gyroscopes, compact, lightweight, multimodal, low-cost, and highly accurate. Wearable …

Contrastive distillation with regularized knowledge for deep model compression on sensor-based human activity recognition

Q Xu, M Wu, X Li, K Mao, Z Chen - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep learning (DL) approaches have been widely applied to sensor-based human activity
recognition (HAR). However, existing approaches neglect to distinguish human activities …