Multi-breath: Separate respiration monitoring for multiple persons with UWB radar

Y Yang, J Cao, X Liu, X Liu - 2019 IEEE 43rd Annual Computer …, 2019 - ieeexplore.ieee.org
Human respiration state is an important indicator to reflect health conditions. Recent
advances in wireless human sensing have enabled device-free respiration monitoring using …

Activity recognition of FMCW radar human signatures using tower convolutional neural networks

A Helen Victoria, G Maragatham - Wireless Networks, 2021 - Springer
Human activity recognition has become an obligatory necessity in day to day life and
possible solutions can be provided with the technological advancement of sensing field …

Human activity classification with radar signal processing and machine learning

M Jia, S Li, J Le Kernec, S Yang… - … conference on UK …, 2020 - ieeexplore.ieee.org
As the number of older adults increases worldwide, new paradigms for indoor activity
monitoring are required to keep people living at home independently longer. Radar-based …

Noninvasive human activity recognition using millimeter-wave radar

C Yu, Z Xu, K Yan, YR Chien, SH Fang… - IEEE Systems …, 2022 - ieeexplore.ieee.org
The millimeter-wave (mmWave) radar technology has attracted significant attention because
it is susceptible to environmental lighting, wall shielding, and privacy concern. This article …

Cross-frequency classification of indoor activities with dnn transfer learning

A Shrestha, C Murphy, I Johnson… - 2019 IEEE Radar …, 2019 - ieeexplore.ieee.org
Remote, non-contact recognition of human motion and activities is central to health
monitoring in assisted living facilities, but current systems face the problems of training …

A non-contact detection method for multi-person vital signs based on IR-UWB radar

X Dang, J Zhang, Z Hao - Sensors, 2022 - mdpi.com
With the vigorous development of ubiquitous sensing technology, an increasing number of
scholars pay attention to non-contact vital signs (eg, Respiration Rate (RR) and Heart Rate …

Radar point clouds processing for human activity classification using convolutional multilinear subspace learning

X Qiao, Y Feng, S Liu, T Shan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Radar-based human activity classification is crucial for applications such as healthcare
monitoring, fall detection, and assisted living due to its superior sensing capabilities and …

SmartWall: Novel RFID-enabled ambient human activity recognition using machine learning for unobtrusive health monitoring

GA Oguntala, RA Abd-Alhameed, NT Ali, YF Hu… - IEEE …, 2019 - ieeexplore.ieee.org
Human activity recognition (HAR) from sensor readings has proved to be an effective
approach in pervasive computing for smart healthcare. Recent approaches in ambient …

A Multidimensional Parallel Convolutional Connected Network Based on Multisource and Multimodal Sensor Data for Human Activity Recognition

Y Wang, H Xu, L Zheng, G Zhao, Z Liu… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Human activity recognition (HAR) technology based on wearables has received increasing
attention in recent years. The traditional methods have used hand-crafted features to …

A hybrid CNN–LSTM network for the classification of human activities based on micro-Doppler radar

J Zhu, H Chen, W Ye - Ieee Access, 2020 - ieeexplore.ieee.org
Many deep learning (DL) models have shown exceptional promise in radar-based human
activity recognition (HAR) area. For radar-based HAR, the raw data is generally converted …