Relevant bibliographies by topics / Vital signs monitoring using radar

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Academic literature on the topic 'Vital signs monitoring using radar'

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Published: 6 September 2023

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Journal articles on the topic "Vital signs monitoring using radar"

1

Kebe, Mamady, Rida Gadhafi, Baker Mohammad, Mihai Sanduleanu, Hani Saleh, and Mahmoud Al-Qutayri. "Human Vital Signs Detection Methods and Potential Using Radars: A Review." Sensors 20, no. 5 (March 6, 2020): 1454. http://dx.doi.org/10.3390/s20051454.

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Continuous monitoring of vital signs, such as respiration and heartbeat, plays a crucial role in early detection and even prediction of conditions that may affect the wellbeing of the patient. Sensing vital signs can be categorized into: contact-based techniques and contactless based techniques. Conventional clinical methods of detecting these vital signs require the use of contact sensors, which may not be practical for long duration monitoring and less convenient for repeatable measurements. On the other hand, wireless vital signs detection using radars has the distinct advantage of not requiring the attachment of electrodes to the subject’s body and hence not constraining the movement of the person and eliminating the possibility of skin irritation. In addition, it removes the need for wires and limitation of access to patients, especially for children and the elderly. This paper presents a thorough review on the traditional methods of monitoring cardio-pulmonary rates as well as the potential of replacing these systems with radar-based techniques. The paper also highlights the challenges that radar-based vital signs monitoring methods need to overcome to gain acceptance in the healthcare field. A proof-of-concept of a radar-based vital sign detection system is presented together with promising measurement results.
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Zhang, Xinyue, Xiuzhu Yang, Yi Ding, Yili Wang, Jialin Zhou, and Lin Zhang. "Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars." Sensors 21, no. 16 (August 16, 2021): 5503. http://dx.doi.org/10.3390/s21165503.

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Vital signs monitoring in physical activity (PA) is of great significance in daily healthcare. Impulse Radio Ultra-WideBand (IR-UWB) radar provides a contactless vital signs detection approach with advantages in range resolution and penetration. Several researches have verified the feasibility of IR-UWB radar monitoring when the target keeps still. However, various body movements are induced by PA, which lead to severe signal distortion and interfere vital signs extraction. To address this challenge, a novel joint chest–abdomen cardiopulmonary signal estimation approach is proposed to detect breath and heartbeat simultaneously using IR-UWB radars. The movements of target chest and abdomen are detected by two IR-UWB radars, respectively. Considering the signal overlapping of vital signs and body motion artifacts, Empirical Wavelet Transform (EWT) is applied on received radar signals to remove clutter and mitigate movement interference. Moreover, improved EWT with frequency segmentation refinement is applied on each radar to decompose vital signals of target chest and abdomen to vital sign-related sub-signals, respectively. After that, based on the thoracoabdominal movement correlation, cross-correlation functions are calculated among chest and abdomen sub-signals to estimate breath and heartbeat. The experiments are conducted under three kinds of PA situations and two general body movements, the results of which indicate the effectiveness and superiority of the proposed approach.
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Li, Zhi, Tian Jin, Yongpeng Dai, and Yongkun Song. "Through-Wall Multi-Subject Localization and Vital Signs Monitoring Using UWB MIMO Imaging Radar." Remote Sensing 13, no. 15 (July 23, 2021): 2905. http://dx.doi.org/10.3390/rs13152905.

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Radar-based non-contact vital signs monitoring has great value in through-wall detection applications. This paper presents the theoretical and experimental study of through-wall respiration and heartbeat pattern extraction from multiple subjects. To detect the vital signs of multiple subjects, we employ a low-frequency ultra-wideband (UWB) multiple-input multiple-output (MIMO) imaging radar and derive the relationship between radar images and vibrations caused by human cardiopulmonary movements. The derivation indicates that MIMO radar imaging with the stepped-frequency continuous-wave (SFCW) improves the signal-to-noise ratio (SNR) critically by the factor of radar channel number times frequency number compared with continuous-wave (CW) Doppler radars. We also apply the three-dimensional (3-D) higher-order cumulant (HOC) to locate multiple subjects and extract the phase sequence of the radar images as the vital signs signal. To monitor the cardiopulmonary activities, we further exploit the VMD algorithm with a proposed grouping criterion to adaptively separate the respiration and heartbeat patterns. A series of experiments have validated the localization and detection of multiple subjects behind a wall. The VMD algorithm is suitable for separating the weaker heartbeat pattern from the stronger respiration pattern by the grouping criterion. Moreover, the continuous monitoring of heart rate (HR) by the MIMO radar in real scenarios shows a strong consistency with the reference electrocardiogram (ECG).
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Yoo, Young-Keun, and Hyun-Chool Shin. "Movement Compensated Driver’s Respiratory Rate Extraction." Applied Sciences 12, no. 5 (March 4, 2022): 2695. http://dx.doi.org/10.3390/app12052695.

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In non-contact vital sign monitoring using radar, radar signal distorted by the surrounding unspecified factors is unsuitable for monitoring vital signs. In order to monitor vital signs accurately, it is essential to compensate for distortion of radar signals caused by surrounding environmental factors. In this paper, we propose a driver vital signal compensation method in driving situations, including the driver’s movements using a frequency-modulated continuous-wave (FMCW) radar. Driver’s movement is quantified from the radar signal and used to set a distortion signal compensation index to compensate for the signal distortion induced in the driving situation that the driver’s movement occurs. The experimental results show that the respiration rate estimated from the radar signal compensated through the proposed method is similar to the actual respiration rate than from the signal before calibration. These results confirm the possibility of using the proposed method in a non-statistic situation and effectiveness in estimating respiration rate reflecting human movement in monitoring vital signs using FMCW radar.
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Lazaro, Antonio, David Girbau, and Ramon Villarino. "ANALYSIS OF VITAL SIGNS MONITORING USING AN IR-UWB RADAR." Progress In Electromagnetics Research 100 (2010): 265–84. http://dx.doi.org/10.2528/pier09120302.

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Turppa, Emmi, Juha M. Kortelainen, Oleg Antropov, and Tero Kiuru. "Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios." Sensors 20, no. 22 (November 14, 2020): 6505. http://dx.doi.org/10.3390/s20226505.

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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.
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Khan, Faheem, Asim Ghaffar, Naeem Khan, and Sung Ho Cho. "An Overview of Signal Processing Techniques for Remote Health Monitoring Using Impulse Radio UWB Transceiver." Sensors 20, no. 9 (April 27, 2020): 2479. http://dx.doi.org/10.3390/s20092479.

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Non-invasive remote health monitoring plays a vital role in epidemiological situations such as SARS outbreak (2003), MERS (2015) and the recently ongoing outbreak of COVID-19 because it is extremely risky to get close to the patient due to the spread of contagious infections. Non-invasive monitoring is also extremely necessary in situations where it is difficult to use complicated wired connections, such as ECG monitoring for infants, burn victims or during rescue missions when people are buried during building collapses/earthquakes. Due to the unique characteristics such as higher penetration capabilities, extremely precise ranging, low power requirement, low cost, simple hardware and robustness to multipath interferences, Impulse Radio Ultra Wideband (IR-UWB) technology is appropriate for non-invasive medical applications. IR-UWB sensors detect the macro as well as micro movement inside the human body due to its fine range resolution. The two vital signs, i.e., respiration rate and heart rate, can be measured by IR-UWB radar by measuring the change in the magnitude of signal due to displacement caused by human lungs, heart during respiration and heart beating. This paper reviews recent advances in IR- UWB radar sensor design for healthcare, such as vital signs measurements of a stationary human, vitals of a non-stationary human, vital signs of people in a vehicle, through the wall vitals measurement, neonate’s health monitoring, fall detection, sleep monitoring and medical imaging. Although we have covered many topics related to health monitoring using IR-UWB, this paper is mainly focused on signal processing techniques for measurement of vital signs, i.e., respiration and heart rate monitoring.
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Lim, Sungmook, Gwang Soo Jang, Wonyoung Song, Baek-hyun Kim, and Dong Hyun Kim. "Non-Contact VITAL Signs Monitoring of a Patient Lying on Surgical Bed Using Beamforming FMCW Radar." Sensors 22, no. 21 (October 25, 2022): 8167. http://dx.doi.org/10.3390/s22218167.

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Respiration and heartrates are important information for surgery. When the vital signs of the patient lying prone are monitored using radar installed on the back of the surgical bed, the surgeon’s movements reduce the accuracy of these monitored vital signs. This study proposes a method for enhancing the monitored vital sign accuracies of a patient lying on a surgical bed using a 60 GHz frequency modulated continuous wave (FMCW) radar system with beamforming. The vital sign accuracies were enhanced by applying a fast Fourier transform (FFT) for range and beamforming which suppress the noise generated at different ranges and angles from the patient’s position. The experiment was performed for a patient lying on a surgical bed with or without surgeon. Comparing a continuous-wave (CW) Doppler radar, the FMCW radar with beamforming improved almost 22 dB of signal-to-interference and noise ratio (SINR) for vital signals. More than 90% accuracy of monitoring respiration and heartrates was achieved even though the surgeon was located next to the patient as an interferer. It was analyzed using a proposed vital signal model included in the radar IF equation.
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Kathuria, Nitin, and Boon-Chong Seet. "24 GHz Flexible Antenna for Doppler Radar-Based Human Vital Signs Monitoring." Sensors 21, no. 11 (May 27, 2021): 3737. http://dx.doi.org/10.3390/s21113737.

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Noncontact monitoring of human vital signs has been an emerging research topic in recent years. A key approach to this monitoring is the use of the Doppler radar concept which enables real-time vital signs detection, resulting in a new class of radar system known as bio-radar. The antennas are a key component of any bio-radar module and their designs should meet the common requirements of bio-radar applications such as high radiation directivity and mechanical flexibility. This paper presents the design of a four-element antenna array on a flexible liquid crystal polymer (LCP) substrate of 100 μm thickness and εr of 3.35. The designed antenna array can be used with a 24 GHz bio-radar for vital signs monitoring in a non-contact manner. It features a relatively compact size of 36.5 × 53 mm2 and measured gain of 5.81 dBi. The two vital signs: breathing rate (BR) and heart rate (HR) of two human subjects are detected with relatively good accuracy using the fabricated antenna array and radio frequency (RF) output power of −3 dBm from a distance of approximately 60 cm. The effect of bending on the antenna performance is also analyzed.
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Schellenberger, Sven, Kilin Shi, Fabian Michler, Fabian Lurz, Robert Weigel, and Alexander Koelpin. "Continuous In-Bed Monitoring of Vital Signs Using a Multi Radar Setup for Freely Moving Patients." Sensors 20, no. 20 (October 15, 2020): 5827. http://dx.doi.org/10.3390/s20205827.

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In hospitals, continuous monitoring of vital parameters can provide valuable information about the course of a patient’s illness and allows early warning of emergencies. To enable such monitoring without restricting the patient’s freedom of movement and comfort, a radar system is attached under the mattress which consists of four individual radar modules to cover the entire width of the bed. Using radar, heartbeat and respiration can be measured without contact and through clothing. By processing the raw radar data, the presence of a patient can be determined and movements are categorized into the classes “bed exit”, “bed entry”, and “on bed movement”. Using this information, the vital parameters can be assessed in sections where the patient lies calmly in bed. In the first step, the presence and movement classification is demonstrated using recorded training and test data. Next, the radar was modified to perform vital sign measurements synchronized to a gold standard device. The evaluation of the individual radar modules shows that, regardless of the lying position of the test person, at least one of the radar modules delivers accurate results for continuous monitoring.
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Dissertations / Theses on the topic "Vital signs monitoring using radar"

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Tariq, Abubakar. "Vital signs monitoring using Doppler radar and on-body antennas." Thesis, University of Birmingham, 2013. http://etheses.bham.ac.uk//id/eprint/4332/.

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The chest of a person moves due to the heart beating and the lungs expanding and contracting. So the chest movement contains information about the heart and breathing rates. This property is used to detect vital signs using Doppler radar and On-Body antennas. These methods can be accurate, cost-effective, portable, comfortable and low profile alternatives to present commercial heart and breathing rate monitoring devices. The 1st method employing Doppler Effect is non-contact. It detects both the heart and breathing rates using the modulated reflected signals from the chest of a person. A parametric study is conducted considering frequency, power and distance to determine the best parameters for maximum accuracy. A small population study is conducted considering 5 people to validate the accuracy and working of Doppler radar as a vital signs monitor. The 2nd method monitors the heart and breathing rates by sensing motion in the near field proximity of an antenna using the antenna’s reflection coefficient. Simulation studies are conducted using CST chest models to verify the principle. An extensive parametric investigation considering frequency, antenna type, power, antenna location on body, body Position, and distances (between chest and antenna) is conducted to find parameters for maximum detection accuracy. A human population study considering 13 people is conducted to establish heart rate and heart rate variability (HRV) measurement feasibility. A signal processing study is also performed and the best algorithms are identified for accurate detection of vital signs. Besides this novel frequency and pattern reconfigurable antennas are proposed and designed for communications and/or vital signs monitoring purposes.
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Chandrasekaran, Vikram. "Measuring Vital Signs Using Smart Phones." Thesis, University of North Texas, 2010. https://digital.library.unt.edu/ark:/67531/metadc33139/.

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Smart phones today have become increasingly popular with the general public for its diverse abilities like navigation, social networking, and multimedia facilities to name a few. These phones are equipped with high end processors, high resolution cameras, built-in sensors like accelerometer, orientation-sensor, light-sensor, and much more. According to comScore survey, 25.3% of US adults use smart phones in their daily lives. Motivated by the capability of smart phones and their extensive usage, I focused on utilizing them for bio-medical applications. In this thesis, I present a new application for a smart phone to quantify the vital signs such as heart rate, respiratory rate and blood pressure with the help of its built-in sensors. Using the camera and a microphone, I have shown how the blood pressure and heart rate can be determined for a subject. People sometimes encounter minor situations like fainting or fatal accidents like car crash at unexpected times and places. It would be useful to have a device which can measure all vital signs in such an event. The second part of this thesis demonstrates a new mode of communication for next generation 9-1-1 calls. In this new architecture, the call-taker will be able to control the multimedia elements in the phone from a remote location. This would help the call-taker or first responder to have a better control over the situation. Transmission of the vital signs measured using the smart phone can be a life saver in critical situations. In today's voice oriented 9-1-1 calls, the dispatcher first collects critical information (e.g., location, call-back number) from caller, and assesses the situation. Meanwhile, the dispatchers constantly face a "60-second dilemma"; i.e., within 60 seconds, they need to make a complicated but important decision, whether to dispatch and, if so, what to dispatch. The dispatchers often feel that they lack sufficient information to make a confident dispatch decision. This remote-media-control described in this system will be able to facilitate information acquisition and decision-making in emergency situations within the 60-second response window in 9-1-1 calls using new multimedia technologies.
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Razzaghi, Elyas, and Hoek Arno Van. "Micro-Shivering Detection : Detection of human micro-shivering using a 77 GHz radar." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-39807.

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Radars have been under steady development to track, identify, image, and classify targets. Modern radar systems, with the help of embedded systems, have additional comprehensive signal processing capabilities. They can extract useful information from very noisy data, e.g. interference from the environment and unwanted echoes which is collectively known as clutter in radar terms. Concerning the healthcare industry, radar applications for detection of vital signs, i.e. breathing and heart rate, have been extensively developed during the last few decades. Modern radar systems are expected to be a large part of non-intrusive monitoring in the coming smart home industry, where vital signs need to be monitored in the currently aging population. The research presented here is to break new ground in the radar-based healthcare technology, enabling detection of cold-induced shivering to such level that the micro-shivering can be clearly identified. To simplify the radar software optimization, a commercially available radar kit with demo application and a muscle model system using a vibration generator is used. The model is quantified through precise measurements. A simulated human body vital sign plus shivering is applied. By optimizing the radar software, the shivering amplitude and frequency are measured.
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"Remote Sensing For Vital Signs Monitoring Using Advanced Radar Signal Processing Techniques." Doctoral diss., 2018. http://hdl.handle.net/2286/R.I.51751.

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abstract: In the past half century, low-power wireless signals from portable radar sensors, initially continuous-wave (CW) radars and more recently ultra-wideband (UWB) radar systems, have been successfully used to detect physiological movements of stationary human beings. The thesis starts with a careful review of existing signal processing techniques and state of the art methods possible for vital signs monitoring using UWB impulse systems. Then an in-depth analysis of various approaches is presented. Robust heart-rate monitoring methods are proposed based on a novel result: spectrally the fundamental heartbeat frequency is respiration-interference-limited while its higher-order harmonics are noise-limited. The higher-order statistics related to heartbeat can be a robust indication when the fundamental heartbeat is masked by the strong lower-order harmonics of respiration or when phase calibration is not accurate if phase-based method is used. Analytical spectral analysis is performed to validate that the higher-order harmonics of heartbeat is almost respiration-interference free. Extensive experiments have been conducted to justify an adaptive heart-rate monitoring algorithm. The scenarios of interest are, 1) single subject, 2) multiple subjects at different ranges, 3) multiple subjects at same range, and 4) through wall monitoring. A remote sensing radar system implemented using the proposed adaptive heart-rate estimation algorithm is compared to the competing remote sensing technology, a remote imaging photoplethysmography system, showing promising results. State of the art methods for vital signs monitoring are fundamentally related to process the phase variation due to vital signs motions. Their performance are determined by a phase calibration procedure. Existing methods fail to consider the time-varying nature of phase noise. There is no prior knowledge about which of the corrupted complex signals, in-phase component (I) and quadrature component (Q), need to be corrected. A precise phase calibration routine is proposed based on the respiration pattern. The I/Q samples from every breath are more likely to experience similar motion noise and therefore they should be corrected independently. High slow-time sampling rate is used to ensure phase calibration accuracy. Occasionally, a 180-degree phase shift error occurs after the initial calibration step and should be corrected as well. All phase trajectories in the I/Q plot are only allowed in certain angular spaces. This precise phase calibration routine is validated through computer simulations incorporating a time-varying phase noise model, controlled mechanic system, and human subject experiment.
Dissertation/Thesis
Doctoral Dissertation Electrical Engineering 2018
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Lopes, Alexandra Sofia Dias. "Bio-Radar Applications for Remote Vital Signs Monitoring." Master's thesis, 2020. http://hdl.handle.net/10362/118695.

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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.
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NGUYEN, THI PHUONG NHAN. "Vital Signs Estimation using Doppler Radar Techniques." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/h23krr.

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碩士
國立中正大學
電機工程研究所
106
Contactless detection of human body vital signs (respiration rate, heartbeat rate, and blood pressure) using a radar system has been a promising area for future research and clinical practice. In this paper, a continuous-wave 2.45 GHz Doppler radar is used for wirelessly measuring a) respiration rate and respiration inter-interval variation, b) heartbeat rate and heartbeat inter-interval variation, and c) the pulse wave transit time for blood pressure estimation. Both the autocorrelation and conventional Fast Fourier Transform (FFT) estimation algorithms are applied to the received radar signals for computing these vital signs in the time domain and frequency domain, respectively. The autocorrelation algorithm achieves the same accurate estimation of vital-sign inter-interval variation, compared with the MIT's segmentation method. The estimated pulse transit time, using traditional two-radars on heart and elbow simultaneously, indicates a relatively feasibility of blood pressure assessment based on 2.45 GHz radar. It is further shown in this thesis that our proposed single-radar on the elbow can detect the blood pressure assessment as accuracy as the two-radar technique.
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Huang, Yu-Chi, and 黃昱齊. "Implementation of 2.4 GHz Digital Beamforming Doppler Radar for Monitoring Vital Signs." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/b9z4hp.

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碩士
國立中山大學
電機工程學系研究所
107
This thesis is devoted to human tracking and vital signs monitoring using a digital beamforming Doppler radar. Passive radar receives the external signal as the transmit signal. The radar of this work uses the continuous-wave signal from the signal generator to verify the experimental feasibility, and then adopts the Wi-Fi signal as the transmit signal to implement the passive radar architecture. The radar relies on baseband processing to detect the direction of the arrived signal. The subject locates at different positions, causing the reflected signal from the subject to reach each antenna with different phase differences. Using this phase difference, the direction of the subject can be estimated and his/her cardiopulmonary movement can be detected. After weighting the phase difference signals and then combining them, the radar can achieve human tracking and vital signs monitoring. However, the DC offset caused by the circuit and clutter often produces the error of direction. Therefore, this work uses two methods to remove the DC offset for reducing the error of direction. Finally, the experimental results are demonstrated and discussed to explore the limitations of this radar architecture and possible improvements for future applications.
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Lee, Che-Hsi, and 李哲熙. "Development of vital signs monitoring system using wireless technologies." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/96763440181757290123.

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碩士
元智大學
機械工程學系
97
In this study, we use Bluetooth technology and 3.5G to develop a mobile vital signs monitoring system, in which user’s blood oxygen, pulse, blood pressure, ECG, and personal photo can be monitored in real-time. Nonin 4100 pulse oximeter, O-star 2.4G blood pressure device, and Alive ECG device are integrated into a notebook computer using Bluetooth interface. Vital signs are transmitted to specific monitoring site and U-care database through HTTP using 3.5G mobile network. ECG signals may be lost during transmission because of instability of 3.5G mobile network. We developed a decentralized transmission structure in which 30-second ECG signals are stored in files locally and then transmitted to the remote host by HTTP request. To evaluate this system, 7 elderly users tested the system in real application scenario. The results showed that the transmission of vital signs were stable. However, blood pressure measurement often failed because of various external factors.
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Silva, Pedro Miguel Alves da. "Clinical deterioration detection for continuous vital signs monitoring using wearable sensors." Master's thesis, 2020. http://hdl.handle.net/10362/115385.

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Surgical patients are at risk of experiencing clinical deterioration events, especially when transferred to general wards during the postoperative period of their hospital stay. Cur rently, such events are detected by combining Early Warning Scores (EWS) with manual and periodical vital signs measurements, performed by nurses every 4 to 6 hours. Hence, deterioration may remain unnoticed for hours, delaying patient treatment, which might lead to increased morbidity and mortality. Also, EWS are inadequate to predict events so physiologically complex. So that early warning of deterioration could be provided, it was investigated the potential of warning systems that combine machine learning-based prediction models with continuous vital signs monitoring, provided by wearable sensors. This dissertation presents the development of such a warning system, fully indepen dent of manual measurements and based on a logistic regression prediction model with 85% sensitivity, 79% precision and 98% specificity. Additionally, a new personalized ap proach to handle missing data periods in vital signs and a novel variation of a RR-interval preprocessing technique were developed. The results obtained revealed a relevant im provement in the detection of deterioration events and a significant reduction in false alarms, when comparing the warning system with a commonly employed EWS (42% sensitivity, 14% precision and 90% specificity). It was also found that the developed sys tem can assess patient’s condition much more frequently and with timely deterioration detection, without even requiring nurses to interrupt their workflow. These findings sup port the idea that these warning systems are reliable, more practical, more appropriate and produce smarter alarms than current methods, making early deterioration detection possible, thus contributing for better patients outcomes. Nonetheless, the performance achieved may yet reveal insufficient for application in real clinical contexts. Therefore, further work is necessary to improve prediction performance to a greater extent and to confirm these systems reliability.
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Wu, Yung-Cheng, and 吳勇成. "Vital Signs Monitoring of Patients in a Hemodialysis Center Using Wireless Sensor Networks." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/97949339780983080964.

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碩士
國立臺灣大學
生物產業機電工程學研究所
97
Intradialytic hypotension (IDH) is a much common complication during a hemodialysis. The prevalence of IDH is about 10-50%. Elderly people, patients with diabetes, and cardiovascular dialysis patients have the highest rate of inci-dences. IDH may lead to nausea, vomiting, or anxiety. In some severe cases, there will be accident like shock and death. Moreover, patients’ physical monitoring is easily interrupted, and medical quality is often compromised, as nurses in a hemodialysis center joggle many tasks at the time. Therefore, the purpose of this paper is to integrate the technologies of wireless sensor networks (WSN) technologies, global systems for mobile communications (GSMs), and a MySQL database to construct an automatic monitoring system to collect physical data during hemodialysis. And an alert can be immediately sent to family members and nurses if IDH occurs. We then apply this wireless monitoring technology to the patients with IDH. This system is applied to an indoor space. The system framework includes two parts: the wireless networks and the controlling platform. During hemodialysis simulations, the average success ratio of physical data transmitting is 94.84%, the average reliability of systolic pressure is 1, of diastolic pressure is 0.89, and of pulse is 0.94, where the testing cases are collected from 6 persons, and the time interval is 2 hours. The loss ratio of physical data results from space constraints and data collision.
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Book chapters on the topic "Vital signs monitoring using radar"

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Rathna, G. N., and Deepchand Meshineni. "Vital Signs Monitoring Using FMCW Radar for Different Body Orientations in the Presence of Random Body Movement." In Proceedings of First International Conference on Computational Electronics for Wireless Communications, 501–9. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6246-1_42.

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Wang, Chao, Lin Shen, Ningxin Yu, and Yangjie Cao. "Multi-targets Vital Signs Detection Using CW Radar." In Computer Science and Education, 205–12. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2443-1_17.

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Khorozovn, O. A., I. V. Krak, A. I. Kulias, V. S. Kasianiuk, W. Wójcik, and A. Tergeusizova. "Monitoring vital signs using fuzzy logic rules." In Information Technology in Medical Diagnostics II, 237–44. London, UK; Boca Raton: CRC Press/Balkema, [2019] | Selected and extended conference papers from Polish, Ukranian and Kazakh scientists.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429057618-28.

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Hamidi, Shahrokh, Safieddin Safavi Naeini, and George Shaker. "An Overview of Vital Signs Monitoring Based on RADAR Technologies." In Sensing Technology, 113–24. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98886-9_9.

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Fioranelli, Francesco, Ronny G. Guendel, Nicolas C. Kruse, and Alexander Yarovoy. "Radar Sensing in Healthcare: Challenges and Achievements in Human Activity Classification & Vital Signs Monitoring." In Bioinformatics and Biomedical Engineering, 492–504. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-34960-7_35.

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Wang, Wen, Yong Wang, Xiaobo Yang, Mu Zhou, and Liangbo Xie. "Vital Signs Detection Using a FMCW Radar Sensor Based on the Discrete Wavelet Transform." In Lecture Notes in Electrical Engineering, 1210–13. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8411-4_159.

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Zhang, Meng, Zhibin Yu, Pang Rong, and Gao Yuan. "A Complete Ensemble Local Mean Decomposition and Its Application in Doppler Radar Vital Signs Monitoring System." In Lecture Notes in Electrical Engineering, 236–44. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9968-0_28.

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Hoang Long, Nguyen Mai, Jong-Jin Kim, and Wan-Young Chung. "A Prototype Wristwatch Device for Monitoring Vital Signs Using Multi-wavelength Photoplethysmography Sensors." In Intelligent Human Computer Interaction, 312–18. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68452-5_32.

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Prakash, R., Siva V. Girish, and A. Balaji Ganesh. "Real-Time Remote Monitoring of Human Vital Signs Using Internet of Things (IoT) and GSM Connectivity." In Proceedings of the International Conference on Soft Computing Systems, 47–56. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2674-1_5.

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Hassan, Maliha, Jannat Binta Alam, Arpa Datta, Anika Thasin Mim, and Md Naimul Islam. "Machine Learning Approach for Predicting COVID-19 Suspect Using Non-contact Vital Signs Monitoring System by RGB Camera." In Proceedings of Sixth International Congress on Information and Communication Technology, 465–73. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2102-4_43.

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Conference papers on the topic "Vital signs monitoring using radar"

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Tariq, A., and H. G. Shiraz. "Doppler radar vital signs monitoring using wavelet transform." In Propagation Conference (LAPC). IEEE, 2010. http://dx.doi.org/10.1109/lapc.2010.5666002.

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Zhao, Yanhua, Vladica Sark, Milos Krstic, and Eckhard Grass. "Multi-Target Vital Signs Remote Monitoring Using mmWave FMCW Radar." In 2021 IEEE Microwave Theory and Techniques in Wireless Communications (MTTW). IEEE, 2021. http://dx.doi.org/10.1109/mttw53539.2021.9607087.

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Ahmad, Adeel, June Chul Roh, Dan Wang, and Aish Dubey. "Vital signs monitoring of multiple people using a FMCW millimeter-wave sensor." In 2018 IEEE Radar Conference (RadarConf18). IEEE, 2018. http://dx.doi.org/10.1109/radar.2018.8378778.

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Wisland, Dag T., Kristian Granhaug, Jan Roar Pleym, Nikolaj Andersen, Stig Stoa, and Hakon A. Hjortland. "Remote monitoring of vital signs using a CMOS UWB radar transceiver." In 2016 14th IEEE International New Circuits and Systems Conference (NEWCAS). IEEE, 2016. http://dx.doi.org/10.1109/newcas.2016.7604841.

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Sacco, G., E. Piuzzi, E. Pittella, and S. Pisa. "Vital Signs Monitoring for Different Chest Orientations Using an FMCW Radar." In 2020 XXXIIIrd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS). IEEE, 2020. http://dx.doi.org/10.23919/ursigass49373.2020.9232333.

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Zhu, N., B. Liu, R. Qi, Z. Chen, S. Xu, and G. Niu. "Vital signs monitoring using an IR-UWB radar based on edge computing." In IET International Radar Conference (IET IRC 2020). Institution of Engineering and Technology, 2021. http://dx.doi.org/10.1049/icp.2021.0806.

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Nosrati, Mehrdad, Shahram Shahsavari, and Negar Tavassolian. "Multi-Target Vital-Signs Monitoring Using a Dual-Beam Hybrid Doppler Radar." In 2018 IEEE International Microwave Biomedical Conference (IMBioC). IEEE, 2018. http://dx.doi.org/10.1109/imbioc.2018.8428942.

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Närväinen, Johanna, Juha Kortelainen, Timo Urhemaa, Mikko Saajanlehto, Kari Bäckman, and Johan Plomp. "HealthGate: unobtrusive home monitoring of vital signs, weight and mobility of the elderly." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003472.

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This paper will discuss the feasibility of a monitoring setup HealthGate, designed to monitor the mobility, vital signs, and weight of an elderly person living in her own apartment. The versatile sensor setup will allow more comprehensive insights than what is currently available. Continuous home monitoring will enable early interventions and actions in e.g. suspected dehydration, mobility problems, and non-optimal or missed medication. The data can be used to form indices of e.g. frailty and sleep quality, to detect changes in health and behavior, and to alert the person, relatives or caregivers of detected and impending problems. Instead of interaction with the user, the setup seeks total unobtrusiveness: invisible or integrated sensors as well as automated measurements and data transmission. This is crucial with persons suffering from severe cognitive impairment: the operation does not rely on user actions and the setup is safe from a curious user. On the other hand, tailored reports can be provided to people who can and want to investigate their own status. The custom-made monitoring system uses three sensor types: a mm-range imaging FMCW radar (1), a seat foil sensor (2), and a novel four-element weight sensor array. The seat and weight sensors are positioned in a favorite armchair and the radar cabinet faces the chair, typically positioned next to the TV. The key events from which the data are recorded are the transitions to and from the chair and the moments sitting still in the in, typically watching TV. The system will monitor heart and breathing rate (both radar and seat foil), weight, and dynamic weight distribution across the sensors under the legs of the chair, as well as movement at and near the chair (radar). Sleep is monitored using a commercial sleep sensor (VTracker 2.0, eLive Ecosystem Ltd., Finland) placed underneath the topping mattress. As the chairs used in individual homes will vary making inter-subject comparisons more difficult, during each home monitoring period, the participants will also perform a guided sitting, standing-up and walking protocol using a similar setup but with a test chair. The 25 participants are residents of a senior community, living independently in their rental apartments but using home care services. The data are collected during a series of two two-week monitoring periods, five participants at a time, starting in November 2022. We will describe the setup and data collection solution as well as show the first multisensor data comparisons and the proposals for characteristic mobility parameters for a sit down - stand up sequence and walk. The quality, reliability and limits of the biosignals and movement parameters derived from the radar data will be discussed. The data will be compared to standard measures of frailty, collected in a controlled test session, consisting of grip force, walking speed, timed sit down – stand up, and agility tests, as well as the frailty index (3) computed from the interRAI-HC assessments collected bi-annually. The daily patterns, biosignal data and daily weight variation will be compared against sleep data and interview data on acute illnesses and other conditions influencing behavior and well-being. Finally, the usability and acceptability of the setup are discussed, based on the interview data collected from the participants and home care nurses.(1) M. Mercuri et al., (2016). Biomedical wireless radar sensor network for indoor emergency situations detection and vital signs monitoring. IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS), pp. 32-35(2) Anttonen, J., & Surakka, V. (2005, April). Emotions and heart rate while sitting on a chair. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 491-499).(3) Faller JW, et al. (2019) Instruments for the detection of frailty syndrome in older adults: A systematic review. PLOS ONE 14(4): e0216166
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Islam, Shekh M. M., Naoyuki Motoyama, Sergio Pacheco, and Victor M. Lubecke. "Non-Contact Vital Signs Monitoring for Multiple Subjects Using a Millimeter Wave FMCW Automotive Radar." In 2020 IEEE/MTT-S International Microwave Symposium (IMS). IEEE, 2020. http://dx.doi.org/10.1109/ims30576.2020.9223838.

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Zhang, Li, Chuanwei Ding, Xudong Zhou, Hong Hong, Changzhi Li, and Xiaohua Zhu. "Body movement cancellation using adaptive filtering technology for radar-based vital sign monitoring." In 2020 IEEE Radar Conference (RadarConf20). IEEE, 2020. http://dx.doi.org/10.1109/radarconf2043947.2020.9266671.

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Reports on the topic "Vital signs monitoring using radar"

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Bracewell, Jeff. Shoreline change at Padre Island National Seashore, Texas: 2017–2021 data summary. National Park Service, December 2021. http://dx.doi.org/10.36967/nrr-2289824.

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In the spring of 2017, 2019, and 2021 the Gulf Coast Network collected shoreline position data at Padre Island National Seashore as a part of the NPS Vital Signs Monitoring Program. Monitoring was conducted following methods detailed in Monitoring Shoreline Position at Gulf Coast Network Parks: Protocol Implementation Plan (PIP; Bracewell 2017). Shoreline change was calculated using the Digital Shoreline Analysis System developed by USGS (Theiler et al. 2008). This report provides a summary of changes in shoreline position at Padre Island NS from May 2017 through May 2021.
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Baron, Lisa. Post-Dorian shoreline change at Cape Hatteras National Seashore: 2019 report. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2282127.

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In 2018 and 2019 the Southeast Coast Network (SECN), with assistance from park staff, collected long-term shoreline monitoring data at Cape Hatteras National Seashore as part of the National Park Service (NPS) Vital Signs Monitoring Program. Monitoring was conducted following methods developed by the NPS Northeast Coastal and Barrier Network and consisted of mapping the high-tide swash line using a Global Positioning System unit in the spring of each year (Psuty et al. 2010). Shoreline change was calculated using the Digital Shoreline Analysis System (DSAS) developed by the United States Geological Survey (USGS; Himmelstoss et al. 2018). Following the same field methods used for monitoring long-term shoreline change, geospatial data were collected as part of the Hurricane Dorian (or Dorian) Incident Response from September 12–16, 2019. This report summarizes the post-Dorian data and the previous two shoreline data collection efforts (spring 2019 and fall 2018).
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Bracewell, Jeff. Shoreline change at Gulf Islands National Seashore, Florida and Mississippi: 2018–2021 data summary. National Park Service, March 2022. http://dx.doi.org/10.36967/nrr-2293103.

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In May and June 2018, and April 2021, the Gulf Coast Network (GULN) surveyed shoreline position at Gulf Islands National Seashore (GUIS) as a part of the NPS Vital Signs Monitoring Program. Monitoring was conducted following methods detailed in Monitoring Shoreline Position at Gulf Coast Network Parks: Protocol Implementation Plan (PIP; Bracewell 2017). Shoreline change was calculated using the Digital Shoreline Analysis System developed by USGS (Theiler et al. 2008). Key findings from this effort are as follows: In Florida, the mean shoreline change rate from 2018 to 2021 was -7.10 meters/year (-23.3 feet[ft]/year) with a standard deviation of 5.01 meters (16.4 ft) with approximately 95% of transects exhibiting landward retreat. In Mississippi, the mean change in island width from 2018 to 2021 was -7.46 meters/year (-24.5 ft/year) with a standard deviation of 12.49 meters (41.0 ft) with approximately 73% of transects exhibiting a loss in width. This project is in the early phases of implementation and will benefit from future surveys to better understand the influence of slight changes in survey timing and other environmental variations.
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Schmidt, Elizabeth. Shoreline change at Fort Matanzas National Monument: 2020–2021 data summary. National Park Service, January 2022. http://dx.doi.org/10.36967/nrds-2290193.

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In 2020 and 2021 the Southeast Coast Network (SECN) collected shoreline data at Fort Matanzas National Monument as a part of the NPS Vital Signs Monitoring Program. Monitoring was conducted following methods developed by the National Park Service Northeast Barrier Coast Network and consisted of mapping the high tide swash line using a global positioning system (GPS) unit in the spring of each year (Psuty et al. 2010). Shoreline change was calculated using the Digital Shoreline Analysis System (DSAS) developed by USGS (Theiler et al. 2008). Key findings from this effort: A mean of 2,255.23 meters (7,399 feet [ft]) of shoreline were mapped from 2020 to 2021 with a mean horizontal precision of 10.73 centimeters (4.2 inches [in]) at Fort Matanzas National Monument from 2020 to 2021. In the annual shoreline change analysis, the mean shoreline distance change from spring 2020 to spring 2021 was -7.40 meters (-24.3 ft) with a standard deviation of 20.24 meters (66.40 ft). The shoreline change distance ranged from -124.73 to 35.59 meters (-409.1 to 116.7 ft). Two erosion areas and one accretion area were identified in the study area beyond the uncertainty of the data (± 10 meters [32.8 ft]). The annual shoreline change from 2020 to 2021 showed erosion on the east and west sides of A1A where the Matanzas Inlet is located. Overall, the most dynamic area of shoreline change within Fort Matanzas National Monument appeared to be on the east and west side of A1A, along the Matanzas River inlet.
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Bracewell, Jeff. Shoreline change at Gulf Islands National Seashore, Florida and Mississippi: 2018–2022 data summary. National Park Service, January 2023. http://dx.doi.org/10.36967/2296901.

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In May and June 2018, April 2021, and April 2022 the Gulf Coast Network (GULN) surveyed shoreline position at Gulf Islands National Seashore (GUIS) as a part of the NPS Vital Signs Monitoring Program. Monitoring was conducted following methods detailed in Monitoring Shoreline Position at Gulf Coast Network Parks: Protocol Implementation Plan (PIP; Bracewell 2017). Shoreline change was calculated using the Digital Shoreline Analysis System developed by USGS (Theiler et al. 2008). Key findings from this effort are as follows: In Florida, the mean shoreline change rate from 2018 to 2022 was -5.14 meters/year (-17.75 feet[ft]/year) with a standard deviation of 4.57 meters (14.99 ft). Approximately 91% of transects exhibited landward retreat. In Mississippi, the mean change in island width from 2018 to 2022 was -7.46 meters/year (-24.5 ft/year) with a standard deviation of 12.49 meters (41.0 ft). Approximately 73% of transects exhibited a loss in width. The 2020 hurricane season was extremely active, causing high shoreline retreat rates from 2018 to 2021. The 2021 hurricane season was much calmer in comparison, and concordantly, rates of shoreline retreat were generally lessened or reversed to shoreline advance between 2021 and 2022. A beach nourishment project on the eastern end of Perdido Key advanced the shoreline an average of 42.2 meters (138.5 ft) within the project area. This report expands on the previous GULN Shoreline Position report (Bracewell 2022a), to document “storminess” and current sea level rise trends. This project is in the early phases of implementation and will benefit from future surveys to better understand the influence of slight changes in survey timing and other environmental variations.
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