Human sensing by using radio frequency signals: A survey on occupancy and activity detection
R Shahbazian, I Trubitsyna - IEEE Access, 2023 - ieeexplore.ieee.org
Applications for human sensing, also known as (human) occupancy detection, include
energy management systems for intelligent buildings, intruder detection, e-health systems …
energy management systems for intelligent buildings, intruder detection, e-health systems …
[PDF][PDF] Deep learning and its applications to WiFi human sensing: A benchmark and a tutorial
WiFi sensing has been evolving rapidly in recent years. Empowered by propagation models
and deep learning methods, many challenging applications are realized such as WiFi-based …
and deep learning methods, many challenging applications are realized such as WiFi-based …
SenseFi: A library and benchmark on deep-learning-empowered WiFi human sensing
Over the recent years, WiFi sensing has been rapidly developed for privacy-preserving,
ubiquitous human-sensing applications, enabled by signal processing and deep-learning …
ubiquitous human-sensing applications, enabled by signal processing and deep-learning …
GaitFi: Robust device-free human identification via WiFi and vision multimodal learning
As an important biomarker for human identification, human gait can be collected at a
distance by passive sensors without subject cooperation, which plays an essential role in …
distance by passive sensors without subject cooperation, which plays an essential role in …
Autofi: Toward automatic wi-fi human sensing via geometric self-supervised learning
Wi-Fi sensing technology has shown superiority in smart homes among various sensors for
its cost-effective and privacy-preserving merits. It is empowered by channel state information …
its cost-effective and privacy-preserving merits. It is empowered by channel state information …
SecureSense: Defending adversarial attack for secure device-free human activity recognition
Deep neural networks have empowered accurate device-free human activity recognition,
which has wide applications. Deep models can extract robust features from various sensors …
which has wide applications. Deep models can extract robust features from various sensors …
[HTML][HTML] Novel statistical time series data augmentation and machine learning based classification of unobtrusive respiration data for respiration Digital Twin model
Digital Twin (DT), a concept of Healthcare (4.0), represents the subject's biological
properties and characteristics in a digital model. DT can help in monitoring respiratory …
properties and characteristics in a digital model. DT can help in monitoring respiratory …
A Novel Digital Twin (DT) model based on WiFi CSI, Signal Processing and Machine Learning for patient respiration monitoring and decision-support
Digital Twin (DT) in Healthcare 4.0 (H4. 0) presents a digital model of the patient with all its
biological properties and characteristics. One of the application areas is patient respiration …
biological properties and characteristics. One of the application areas is patient respiration …
ResMon: Domain-Adaptive Wireless Respiration State Monitoring via Few-Shot Bayesian Deep Learning
Under the outbreak of the COVID-19 pandemic, respiration state monitoring plays an
important role in assisting respiratory disease diagnosis and treatment. Thanks to the …
important role in assisting respiratory disease diagnosis and treatment. Thanks to the …
Contactless Respiration Monitoring using Wi-Fi and Artificial Neural Network Detection Method
Detecting respiration in a non-intrusive manner is beneficial not only for convenience but
also for cases where the traditional ways cannot be applied. This paper presents a novel …
also for cases where the traditional ways cannot be applied. This paper presents a novel …