Noncontact Vital Signs Detection

Human health condition can be accessed by measurement of vital signs, i.e., respiratory rate (RR), heart rate (HR), blood oxygen level, temperature and blood pressure. Due to drawbacks of contact sensors in measurement, non-contact sensors such as imaging photoplethysmogram (IPPG) and Doppler radar system have been proposed for cardiorespiratory rates detection by researchers.The UWB pulse Doppler radars provide high resolution range-time-frequency information. It is bestowed with advantages of low transmitted power, through-wall capabilities, and high resolution in localization. However, the poor signal to noise ratio (SNR) makes it challenging for UWB radar systems to accurately detect the heartbeat of a subject. To solve the problem, phased-methods have been proposed to extract the phase variations in the reflected pulses modulated by human tiny thorax motions. Advance signal processing method, i.e., state space method, can not only be used to enhance SNR of human vital signs detection, but also enable the micro-Doppler trajectories extraction of walking subject from UWB radar data.Stepped Frequency Continuous Wave (SFCW) radar is an alternative technique useful to remotely monitor human subject activities. Compared with UWB pulse radar, it relieves the stress on requirement of high sampling rate analog-to-digital converter (ADC) and possesses higher signal-to-noise-ratio (SNR) in vital signs detection. However, conventional SFCW radar suffers from long data acquisition time to step over many frequencies. To solve this problem, multi-channel SFCW radar has been proposed to step through different frequency bandwidths simultaneously. Compressed sensing (CS) can further reduce the data acquisition time by randomly stepping through 20% of the original frequency steps.In this work, SFCW system is implemented with low cost, off-the-shelf surface mount components to make the radar sensors portable. Experimental results collected from both pulse and SFCW radar systems have been validated with commercial contact sensors and satisfactory results are shown

Contactless Heart Rate Detection Using MM-Wave Radar Systems Advancements

In recent years, there has been a significant surge in the development of non-contact methods for detecting heart and breathing rates. Various Millimeter-wave (MM-wave) radar systems, operating at different frequency bands like 10 GHz, 24 GHz, 77 GHz, and 122 GHz, have been effectively deployed for this purpose. This paper explores the vital application of contactless systems in the medical field, particularly during disasters and epidemics. These systems are crucial for detecting the heart and breathing rates of individuals trapped under debris, in military operations, long-term vital sign monitoring in hospitals, and aiding the elderly in public spaces. Consequently, our focus is on heart and breathing rate detection using radar systems. This paper highlights the significance of capturing the electrical representation of the heart signal. This approach is known for its trustworthiness and accuracy in identifying various medical conditions. Furthermore, a traditional method based on Fourier transform is presented for heart and respiration rate estimation. This method leverages the direct proportionality between heart and breathing rates and the frequencies of raw radar signals. To estimate the breathing rate, it identifies the maximum peak within the frequency range of 0.15 to 0.4 Hz in the frequency domain and multiplies the corresponding frequency by 60 to obtain the rate per minute. For heart rate estimation, it detects the maximum peak within the frequency range of 0.8 to 2 Hz and calculates the rate per minute accordingly

Contactless Heart Rate Detection Using MM-Wave Radar Systems Advancements

In recent years, there has been a significant surge in the development of non-contact methods for detecting heart and breathing rates. Various Millimeter-wave (MM-wave) radar systems, operating at different frequency bands like 10 GHz, 24 GHz, 77 GHz, and 122 GHz, have been effectively deployed for this purpose. This paper explores the vital application of contactless systems in the medical field, particularly during disasters and epidemics. These systems are crucial for detecting the heart and breathing rates of individuals trapped under debris, in military operations, long-term vital sign monitoring in hospitals, and aiding the elderly in public spaces. Consequently, our focus is on heart and breathing rate detection using radar systems. This paper highlights the significance of capturing the electrical representation of the heart signal. This approach is known for its trustworthiness and accuracy in identifying various medical conditions. Furthermore, a traditional method based on Fourier transform is presented for heart and respiration rate estimation. This method leverages the direct proportionality between heart and breathing rates and the frequencies of raw radar signals. To estimate the breathing rate, it identifies the maximum peak within the frequency range of 0.15 to 0.4 Hz in the frequency domain and multiplies the corresponding frequency by 60 to obtain the rate per minute. For heart rate estimation, it detects the maximum peak within the frequency range of 0.8 to 2 Hz and calculates the rate per minute accordingly

Doppler radar-based non-contact health monitoring for obstructive sleep apnea diagnosis: A comprehensive review

Today’s rapid growth of elderly populations and aging problems coupled with the prevalence of obstructive sleep apnea (OSA) and other health related issues have affected many aspects of society. This has led to high demands for a more robust healthcare monitoring, diagnosing and treatments facilities. In particular to Sleep Medicine, sleep has a key role to play in both physical and mental health. The quality and duration of sleep have a direct and significant impact on people’s learning, memory, metabolism, weight, safety, mood, cardio-vascular health, diseases, and immune system function. The gold-standard for OSA diagnosis is the overnight sleep monitoring system using polysomnography (PSG). However, despite the quality and reliability of the PSG system, it is not well suited for long-term continuous usage due to limited mobility as well as causing possible irritation, distress, and discomfort to patients during the monitoring process. These limitations have led to stronger demands for non-contact sleep monitoring systems. The aim of this paper is to provide a comprehensive review of the current state of non-contact Doppler radar sleep monitoring technology and provide an outline of current challenges and make recommendations on future research directions to practically realize and commercialize the technology for everyday usage

Study of physiological and structural variability in the acquisition of vital signs with Bio Radar

Dissertação para obtenção do Grau de Mestre em Engenharia Informática e de ComputadoresThe monitoring of vital signals is usually carried out by sensors and electrodes. However, it may not be viable or the best solution for people with burn tissues or with more delicate skin, not to mention cases with infectious diseases, where contact should be kept to a minimum. Thus, vital signs monitoring using radar (Bio-Radar) has become a hot topic of research and development. Several studies state that there is variability in vital signs between people. However, in the Bio-Radar area, these issues have not been addressed. In this regard, this dissertation intends to verify if it is possible to evaluate the gender, age, Body Mass Index (BMI), and Chest Wall Perimeter (CWP) through the use of radar signals, namely Bio-Radar, used to the vital signs acquisition. In order to achieve this goal, the vital signs of 92 people (46 females and 46 males), aged between 18 and 50 years old were acquired. With this dataset, it was possible to develop a statistical study of relevant characteristics extracted from the signals. Later, three Machine Learning (ML) algorithms, namely Support Vector Machine (SVM), KNearest Neighbor (KNN) and Random Forest, were trained to identify gender, age, BMI and CWP. Finally, the relation between the respiratory amplitude and the respiratory rhythm is analyzed.A monitorização de sinais vitais e maioritariamente realizada com recurso a sensores e elétrodos. Contudo, pode não ser a forma mais viável ou a melhor solução para pessoas com tecidos queimados ou com pele mais delicada, assim como os casos de doenças infeciosas, onde o contacto deve ser mantido a um nível mínimo. Assim, a monitorização de sinais vitais utilizando radar (Bio-Radar) tornou-se num tema de investigação e desenvolvimento. Vários estudos indicam que existe variabilidade nos sinais vitais entre as pessoas. No entanto, na área do Bio-Radar, estas questões não têm vindo a ser abordadas. Neste sentido, esta dissertação pretende verificar se e possível avaliar o sexo, idade, Índice de Massa Corporal (IMC), e Perímetro da Caixa torácica (PCT) através da utilização de sinais de radar, nomeadamente Bio-Radar, utilizados para a aquisição de sinais vitais. Para atingir este objectivo, foram adquiridos os sinais vitais de 92 pessoas (46 mulheres e 46 homens), com idades compreendidas entre os 18 e os 50 anos. Com este conjunto de dados, foi possível desenvolver um estudo estatístico das características relevantes extraídas dos sinais. Mais tarde, três algoritmos de Machine Learning (ML), nomeadamente Support Vector Machine (SVM), K-Nearest Neighbor (KNN) e Random Forest, foram treinados para identificar o género, idade, IMC e PCT. Finalmente, e analisada a relação entre a amplitude respiratória e o ritmo respiratório.N/

Bio-Radar Applications for Remote Vital Signs Monitoring

Nowadays, most vital signs monitoring techniques used in a medical context and/or daily life routines require direct contact with skin, which can become uncomfortable or even impractical to be used regularly. Radar technology has been appointed as one of the most promising contactless tools to overcome these hurdles. However, there is a lack of studies that cover a comprehensive assessment of this technology when applied in real-world environments. This dissertation aims to study radar technology for remote vital signs monitoring, more specifically, in respiratory and heartbeat sensing. Two off-the-shelf radars, based on impulse radio ultra-wideband and frequency modu lated continuous wave technology, were customized to be used in a small proof of concept experiment with 10 healthy participants. Each subject was monitored with both radars at three different distances for two distinct conditions: breathing and voluntary apnea. Signals processing algorithms were developed to detect and estimate respiratory and heartbeat parameters, assessed using qualitative and quantitative methods. Concerning respiration, a minimum error of 1.6% was found when radar respiratory peaks signals were directly compared with their reference, whereas a minimum mean absolute error of 0.3 RPM was obtained for the respiration rate. Concerning heartbeats, their expression in radar signals was not as clear as the respiration ones, however a minimum mean absolute error of 1.8 BPM for heartbeat was achieved after applying a novel selective algorithm developed to validate if heart rate value was estimated with reliability. The results proved the potential for radars to be used in respiratory and heartbeat contactless sensing, showing that the employed methods can be already used in some mo tionless situations. Notwithstanding, further work is required to improve the developed algorithms in order to obtain more robust and accurate systems.Atualmente, a maioria das técnicas usadas para a monitorização de sinais vitais em contexto médicos e/ou diário requer contacto direto com a pele, o que poderá tornar-se incómodo ou até mesmo inviável em certas situações. A tecnologia radar tem vindo a ser apontada como uma das mais promissoras ferramentas para medição de sinais vitais à distância e sem contacto. Todavia, são necessários mais estudos que permitam avaliar esta tecnologia quando aplicada a situações mais reais. Esta dissertação tem como objetivo o estudo da tecnologia radar aplicada no contexto de medição remota de sinais vitais, mais concretamente, na medição de atividade respiratória e cardíaca. Dois aparelhos radar, baseados em tecnologia banda ultra larga por rádio de impulso e em tecnologia de onda continua modulada por frequência, foram configurados e usados numa prova de conceito com 10 participantes. Cada sujeito foi monitorizado com cada um dos radar em duas situações distintas: respirando e em apneia voluntária. Algorit mos de processamento de sinal foram desenvolvidos para detetar e estimar parâmetros respiratórios e cardíacos, avaliados através de métodos qualitativos e quantitativos. Em relação à respiração, o menor erro obtido foi de 1,6% quando os sinais de radar respiratórios foram comparados diretamente com os sinais de referência, enquanto que, um erro médio absoluto mínimo de 0,3 RPM foi obtido para a estimação da frequência respiratória via radar. A expressão cardíaca nos sinais radar não se revelou tão evidente como a respiratória, no entanto, um erro médio absoluto mínimo de 1,8 BPM foi obtido para a estimação da frequência cardíaca após a aplicação de um novo algoritmo seletivo, desenvolvido para validar a confiança dos valores obtidos. Os resultados obtidos provaram o potencial do uso de radares na medição de atividade respiratória e cardíaca sem contacto, sendo esta tecnologia viável de ser implementada em situações onde não existe muito movimento. Não obstante, os algoritmos desenvolvidos devem ser aperfeiçoados no futuro de forma a obter sistemas mais robustos e precisos

Doppler Radar Techniques for Distinct Respiratory Pattern Recognition and Subject Identification.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

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

Single-Tone Doppler Radar System for Human Respiratory Monitoring

Human respiration activities can be identified from the chest wall movement. In developing a non-contacting sensor for human respiration, the chest wall movement can be detected as a Doppler shift. Therefore, the Doppler radar is potential to be implemented for the non-contacting sensor previously mention. In this paper, the Single-Tone Doppler radar which operates at 10 GHz has been studied and proposed for detecting human respiration. The simulation experimental is performed for investigating the capability of the proposed method in detecting the human respiration parameter such as respiration rate and respiration amplitude. The results show that the proposed method is capable to extract the human respiration parameter