Machine learning for healthcare radars: Recent progresses in human vital sign measurement and activity recognition
The unprecedented non-contact, non-invasive, and privacy-preserving nature of radar
sensors has enabled various healthcare applications, including vital sign monitoring, fall …
sensors has enabled various healthcare applications, including vital sign monitoring, fall …
Real-time human motion behavior detection via CNN using mmWave radar
A real-time behavior detection system using millimeter wave radar is presented in this
article. Radar is used to sense the micro-Doppler information of targets. A convolution neural …
article. Radar is used to sense the micro-Doppler information of targets. A convolution neural …
Fall detection with UWB radars and CNN-LSTM architecture
Fall detection is a major challenge for researchers. Indeed, a fall can cause injuries such as
femoral neck fracture, brain hemorrhage, or skin burns, leading to significant pain. However …
femoral neck fracture, brain hemorrhage, or skin burns, leading to significant pain. However …
Human activity classification with radar: Optimization and noise robustness with iterative convolutional neural networks followed with random forests
The accurate classification of activity patterns based on radar signatures is still an open
problem and is a key to detect anomalous behavior for security and health applications. This …
problem and is a key to detect anomalous behavior for security and health applications. This …
Fusion of wearable and contactless sensors for intelligent gesture recognition
A novel approach of fusing datasets from multiple sensors using a hierarchical support
vector machine (HSVM) algorithm is presented. The validation of this method is …
vector machine (HSVM) algorithm is presented. The validation of this method is …
A multisensory approach for remote health monitoring of older people
Growing life expectancy and increasing incidence of multiple chronic health conditions are
significant societal challenges. Different technologies have been proposed to address these …
significant societal challenges. Different technologies have been proposed to address these …
Human activity classification based on micro-Doppler signatures separation
X Qiao, MG Amin, T Shan, Z Zeng… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Human activity classification based on micro-Doppler (mD) signatures finds applications in
surveillance, search and rescue operations, and healthcare. In this article, we propose a …
surveillance, search and rescue operations, and healthcare. In this article, we propose a …
A three-stage low-complexity human fall detection method using IR-UWB radar
M Chen, Z Yang, J Lai, P Chu, J Lin - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
This paper proposes a novel three-stage low-complexity human fall detection method using
an impulse radio ultra-wideband (IR-UWB) radar. The core idea lies in the three cascaded …
an impulse radio ultra-wideband (IR-UWB) radar. The core idea lies in the three cascaded …
A dual generation adversarial network for human motion detection using micro-Doppler signatures
Radar sensors and micro-Doppler signatures have been widely used to recognize human
motions. Apart from the motion classification task, human motion detection has attracted …
motions. Apart from the motion classification task, human motion detection has attracted …
[HTML][HTML] Comparative Analysis of Audio Processing Techniques on Doppler Radar Signature of Human Walking Motion Using CNN Models
Artificial intelligence (AI) radar technology offers several advantages over other
technologies, including low cost, privacy assurance, high accuracy, and environmental …
technologies, including low cost, privacy assurance, high accuracy, and environmental …