Patient activity recognition using radar sensors and machine learning
Indoor human activity recognition is actively studied as part of creating various intelligent
systems with applications in smart home and office, smart health, internet of things, etc …
systems with applications in smart home and office, smart health, internet of things, etc …
A Comparative Study on Recent Progress of Machine Learning-Based Human Activity Recognition with Radar
K Papadopoulos, M Jelali - Applied Sciences, 2023 - mdpi.com
The importance of radar-based human activity recognition has increased significantly over
the last two decades in safety and smart surveillance applications due to its superiority in …
the last two decades in safety and smart surveillance applications due to its superiority in …
Activity classification based on feature fusion of FMCW radar human motion micro-Doppler signatures
FJ Abdu, Y Zhang, Z Deng - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Fall is a challenging task that poses a great danger to the elderly person's health as they
carry out their daily routines and activities and could lead to serious injuries, long …
carry out their daily routines and activities and could lead to serious injuries, long …
OPERAnet, a multimodal activity recognition dataset acquired from radio frequency and vision-based sensors
This paper presents a comprehensive dataset intended to evaluate passive Human Activity
Recognition (HAR) and localization techniques with measurements obtained from …
Recognition (HAR) and localization techniques with measurements obtained from …
Radar-based human activity recognition with adaptive thresholding towards resource constrained platforms
Radar systems are increasingly being employed in healthcare applications for human
activity recognition due to their advantages in terms of privacy, contactless sensing, and …
activity recognition due to their advantages in terms of privacy, contactless sensing, and …
State-of-the-art radar technology for remote human fall detection: a systematic review of techniques, trends, and challenges
Human falls occur rarely; however, they can lead to severe consequences if not addressed
immediately. With the rise of nuclear families, there has been a significant increase in the …
immediately. With the rise of nuclear families, there has been a significant increase in the …
Discrete human activity recognition and fall detection by combining FMCW RADAR data of heterogeneous environments for independent assistive living
Human activity monitoring is essential for a variety of applications in many fields, particularly
healthcare. The goal of this research work is to develop a system that can effectively detect …
healthcare. The goal of this research work is to develop a system that can effectively detect …
Radar-based human activity recognition combining range–time–Doppler maps and range-distributed-convolutional neural networks
WY Kim, DH Seo - IEEE Transactions on Geoscience and …, 2022 - ieeexplore.ieee.org
Recently, radar-based human activity recognition (HAR) has attracted the attention of
researchers as it has been proven that a deep learning (DL) model can be automatically …
researchers as it has been proven that a deep learning (DL) model can be automatically …
The Human Activity Radar Challenge: Benchmarking Based on the 'Radar Signatures of Human Activities' Dataset From Glasgow University
Radar is an extremely valuable sensing technology for detecting moving targets and
measuring their range, velocity, and angular positions. When people are monitored at home …
measuring their range, velocity, and angular positions. When people are monitored at home …
Cross-frequency training with adversarial learning for radar micro-Doppler signature classification (Rising Researcher)
Deep neural networks have become increasingly popular in radar micro-Doppler
classification; yet, a key challenge, which has limited potential gains, is the lack of large …
classification; yet, a key challenge, which has limited potential gains, is the lack of large …