Non Contact Heart Monitoring

Electrocardiograms are one of the most widely used methods for evaluating the structure-function relationships of the heart in health and disease. This book is the first of two volumes which reviews recent advancements in electrocardiography. This volume lays the groundwork for understanding the technical aspects of these advancements. The five sections of this volume, Cardiac Anatomy, ECG Technique, ECG Features, Heart Rate Variability and ECG Data Management, provide comprehensive reviews of advancements in the technical and analytical methods for interpreting and evaluating electrocardiograms. This volume is complemented with anatomical diagrams, electrocardiogram recordings, flow diagrams and algorithms which demonstrate the most modern principles of electrocardiography. The chapters which form this volume describe how the technical impediments inherent to instrument-patient interfacing, recording and interpreting variations in electrocardiogram time intervals and morphologies, as well as electrocardiogram data sharing have been effectively overcome. The advent of novel detection, filtering and testing devices are described. Foremost, among these devices are innovative algorithms for automating the evaluation of electrocardiograms. Permanenet links: Full chapter: http://www.intechopen.com/articles/show/title/non-contact-heart-monitoring Book: http://www.intechopen.com/books/show/title/advances-in-electrocardiograms-methods-and-analysi

Radar monitoring of heartbeats and respiration

This thesis addresses the use of radar for heartbeat and respiration monitoring. Medical radar can be used for detecting vital signs at distances up to several meters. A medical radar works by transmitting electromagnetic waves towards a person, and receiving echoes reflected off the person. Vital signs appear as modulations in the radar data in period with the heartbeats and respiration. We have measured and analyzed these modulations. The ability to detect human heartbeats from a distance can be used for monitoring patients’ heartbeats without the need of attaching the measurement equipment to the patient. A radar system can be placed over a bed, integrated in a mattress or chair or used for non-intrusive home monitoring. It could also be used as an alternative to the diagnostic monitoring tools of today. In this thesis, the understanding of radar heartbeat detection is explored. Although heartbeats and respiration monitoring using radar have been reported many times before, the optimal frequencies, waveforms and aspect angle of detection were not known. We have described the vital signs modulations as functions of frequency and aspect angle, and found both narrowband and ultra wideband radar to be suited for the task. In addition to quantizing the modulations, an experimental approach to understanding why heartbeat and respiration detection with radar is possible was made. We found that small body surface movements are the cause of the observed heartbeat modulations in radar data, discarding the theory that reflections from internal body organs are seen. On-body radar have been used as well, and a closer connection between the actual movements of the heart and the radar recordings were found than what is achievable using remote radar. With on-body radar and the processing presented in this thesis, details of the heart mechanics can be identified using radar. It is also possible to see changes in the measured waveform when the pulse and blood pressure of the person changes

Emotion Recognition using Wireless Signals

This paper demonstrates a new technology that can infer a person's emotions from RF signals reflected off his body. EQ-Radio transmits an RF signal and analyzes its reflections off a person's body to recognize his emotional state (happy, sad, etc.). The key enabler underlying EQ-Radio is a new algorithm for extracting the individual heartbeats from the wireless signal at an accuracy comparable to on-body ECG monitors. The resulting beats are then used to compute emotion-dependent features which feed a machine-learning emotion classifier. We describe the design and implementation of EQ-Radio, and demonstrate through a user study that its emotion recognition accuracy is on par with state-of-the-art emotion recognition systems that require a person to be hooked to an ECG monitor. Keywords: Wireless Signals; Wireless Sensing; Emotion Recognition; Affective Computing; Heart Rate VariabilityNational Science Foundation (U.S.)United States. Air Forc

A CNN based Multifaceted Signal Processing Framework for Heart Rate Proctoring Using Millimeter Wave Radar Ballistocardiography

The recent pandemic has refocused the medical world's attention on the diagnostic techniques associated with cardiovascular disease. Heart rate provides a real-time snapshot of cardiovascular health. A more precise heart rate reading provides a better understanding of cardiac muscle activity. Although many existing diagnostic techniques are approaching the limits of perfection, there remains potential for further development. In this paper, we propose MIBINET, a convolutional neural network for real-time proctoring of heart rate via inter-beat-interval (IBI) from millimeter wave (mm-wave) radar ballistocardiography signals. This network can be used in hospitals, homes, and passenger vehicles due to its lightweight and contactless properties. It employs classical signal processing prior to fitting the data into the network. Although MIBINET is primarily designed to work on mm-wave signals, it is found equally effective on signals of various modalities such as PCG, ECG, and PPG. Extensive experimental results and a thorough comparison with the current state-of-the-art on mm-wave signals demonstrate the viability and versatility of the proposed methodology. Keywords: Cardiovascular disease, contactless measurement, heart rate, IBI, mm-wave radar, neural networkComment: 13 pages, 10 figures, Submitted to Elsevier's Array Journa

Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios

Remote monitoring of vital signs for studying sleep is a user-friendly alternative to monitoring with sensors attached to the skin. For instance, remote monitoring can allow unconstrained movement during sleep, whereas detectors requiring a physical contact may detach and interrupt the measurement and affect sleep itself. This study evaluates the performance of a cost-effective frequency modulated continuous wave (FMCW) radar in remote monitoring of heart rate and respiration in scenarios resembling a set of normal and abnormal physiological conditions during sleep. We evaluate the vital signs of ten subjects in different lying positions during various tasks. Specifically, we aim for a broad range of both heart and respiration rates to replicate various real-life scenarios and to test the robustness of the selected vital sign extraction methods consisting of fast Fourier transform based cepstral and autocorrelation analyses. As compared to the reference signals obtained using Embla titanium, a certified medical device, we achieved an overall relative mean absolute error of 3.6% (86% correlation) and 9.1% (91% correlation) for the heart rate and respiration rate, respectively. Our results promote radar-based clinical monitoring by showing that the proposed radar technology and signal processing methods accurately capture even such alarming vital signs as minimal respiration. Furthermore, we show that common parameters for heart rate variability can also be accurately extracted from the radar signal, enabling further sleep analyses.publishedVersionPeer reviewe

Design and Implementation of a Stepped Frequency Continuous Wave Radar System for Biomedical Applications

There is a need to detect vital signs of human (e.g., the respiration and heart-beat rate) with noncontact method in a number of applications such as search and rescue operation (e.g. earthquakes, fire), health monitoring of the elderly, performance monitoring of athletes Ultra-wideband radar system can be utilized for noncontact vital signs monitoring and tracking of various human activities of more than one subject. Therefore, a stepped-frequency continuous wave radar (SFCW) system with wideband performance is designed and implemented for Vital signs detection and fall events monitoring. The design of the SFCW radar system is firstly developed using off-the-shelf discrete components. Later, the system is implemented using surface mount components to make it portable with low cost. The measurement result is proved to be accurate for both heart rate and respiration rate detection within ±5% when compared with contact measurements. Furthermore, an electromagnetic model has been developed using a multi-layer dielectric model of the human subject to validate the experimental results. The agreement between measured and simulated results is good for distances up to 2 m and at various subjects’ orientations with respect to the radar, even in the presence of more than one subject. The compressive sensing (CS) technique is utilized to reduce the size of the acquired data to levels significantly below the Nyquist threshold. In our demonstration, we use phase information contained in the obtained complex high-resolution range profile (HRRP) to derive the motion characteristics of the human. The obtained data has been successfully utilized for non-contact walk, fall and limping detection and healthcare monitoring. The effectiveness of the proposed method is validated using measured results

A dataset of clinically recorded radar vital signs with synchronised reference sensor signals

Using Radar it is possible to measure vital signs through clothing or a mattress from the distance. This allows for a very comfortable way of continuous monitoring in hospitals or home environments. The dataset presented in this article consists of 24 h of synchronised data from a radar and a reference device. The implemented continuous wave radar system is based on the Six-Port technology and operates at 24 GHz in the ISM band. The reference device simultaneously measures electrocardiogram, impedance cardiogram and non-invasive continuous blood pressure. 30 healthy subjects were measured by physicians according to a predefined protocol. The radar was focused on the chest while the subjects were lying on a tilt table wired to the reference monitoring device. In this manner five scenarios were conducted, the majority of them aimed to trigger hemodynamics and the autonomic nervous system of the subjects. Using the database, algorithms for respiratory or cardiovascular analysis can be developed and a better understanding of the characteristics of the radar-recorded vital signs can be gained