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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 …
thus reducing the risk of serious injuries. With the development of society and increasing …
Human activity recognition using binary sensors: A systematic review
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 …
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 …
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
Abstract Human Activity Recognition (HAR) and fall detection, as applications within the field
of biomedical signal processing, are increasingly pivotal in enhancing patient care …
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
Recent advances in wearable systems have made inertial sensors, such as accelerometers
and gyroscopes, compact, lightweight, multimodal, low-cost, and highly accurate. Wearable …
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
Deep learning (DL) approaches have been widely applied to sensor-based human activity
recognition (HAR). However, existing approaches neglect to distinguish human activities …
recognition (HAR). However, existing approaches neglect to distinguish human activities …