Related papers: Noncontact Respiratory Anomaly Detection Using Inf…
Radio frequency (RF) signals have facilitated the development of non-contact human monitoring tasks, such as vital signs measurement, activity recognition, and user identification. In some specific scenarios, an RF signal analysis framework…
Advances in machine learning and deep neural networks for object detection, coupled with lower cost and power requirements of cameras, led to promising vision-based solutions for sUAS detection. However, solely relying on the visible…
In this paper, we first present a single-input, multiple-output convolutional neural network that can estimate both heart rate and respiration rate simultaneously by exploiting the underlying link between heart rate and respiration rate.…
In recent years, WiFi sensing has been recognized as a promising technology to bring respiratory monitoring into everyday homes, thanks to its contactless nature and ubiquitous availability. However, existing WiFi-based respiratory…
Vital sign (breathing and heartbeat) monitoring is essential for patient care and sleep disease prevention. Most current solutions are based on wearable sensors or cameras; however, the former could affect sleep quality, while the latter…
This paper is the first to present a novel, non-contact method that utilizes orthogonal frequency division multiplexing (OFDM) signals (of frequency 5.23 GHz, emitted by a software defined radio) to radio-expose the pulmonary patients in…
Respiratory ailments are increasing globally at an alarming rate and are currently one of the leading factors of death and infirmity worldwide. Among respiratory diseases, those linked to poor air quality and pollutants are increasing at a…
Non-invasive in vivo sensing of the lung with light would help diagnose and monitor pulmonary disorders (caused by e.g. COVID-19, emphysema, immature lung tissue in infants). We investigated the possibility to probe the lung with time…
This paper presents a two-dimensional phase extraction system using passive WiFi sensing to monitor three basic elderly care activities including breathing rate, essential tremor and falls. Specifically, a WiFi signal is acquired through…
WiFi channel state information (CSI) has emerged as a plausible modality for sensing different human vital signs, i.e. respiration and body motion, as a function of modulated wireless signals that travel between WiFi devices. Although a…
The purpose of this study is to provide means to physicians for automated and fast recognition of airways diseases. In this work, we mainly focus on measures that can be easily recorded using a spirometer. The signals used in this framework…
The ability of sensing breathing is becoming an increasingly important function for technology that aims at supporting both psychological and physical wellbeing. We demonstrate ThermSense, a new breathing sensing platform based on…
Respiration is a critical vital sign for infants, and continuous respiratory monitoring is particularly important for newborns. However, neonates are sensitive and contact-based sensors present challenges in comfort, hygiene, and skin…
Breathing rate is a vital health metric that is an invaluable indicator of the overall health of a person. In recent years, the non-contact measurement of health signals such as breathing rate has been a huge area of development, with a…
Coronavirus Disease 2019 (COVID-19) has become a serious global epidemic in the past few months and caused huge loss to human society worldwide. For such a large-scale epidemic, early detection and isolation of potential virus carriers is…
Radar-based respiratory measurement is a promising tool for the noncontact detection of sleep apnea. Our team has reported that apnea events can be accurately detected using the statistical characteristics of the amplitude of respiratory…
Respiratory disease, the third leading cause of deaths globally, is considered a high-priority ailment requiring significant research on identification and treatment. Stethoscope-recorded lung sounds and artificial intelligence-powered…
Passive hyperspectral longwave infrared measurements are remarkably informative about the surroundings. Remote object material and temperature determine the spectrum of thermal radiance, and range, air temperature, and gas concentrations…
Respiratory diseases remain major global health challenges, and traditional auscultation is often limited by subjectivity, environmental noise, and inter-clinician variability. This study presents an explainable multimodal deep learning…
Objective: Non-contact physiological measurement is a growing research area that allows capturing vital signs such as heart rate (HR) and breathing rate (BR) comfortably and unobtrusively with remote devices. However, most of the approaches…