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Liebetruth M, Kehe K, Steinritz D, Sammito S. Systematic Literature Review Regarding Heart Rate and Respiratory Rate Measurement by Means of Radar Technology. SENSORS (BASEL, SWITZERLAND) 2024; 24:1003. [PMID: 38339721 PMCID: PMC10857015 DOI: 10.3390/s24031003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 01/23/2024] [Accepted: 01/30/2024] [Indexed: 02/12/2024]
Abstract
The use of radar technology for non-contact measurement of vital parameters is increasingly being examined in scientific studies. Based on a systematic literature search in the PubMed, German National Library, Austrian Library Network (Union Catalog), Swiss National Library and Common Library Network databases, the accuracy of heart rate and/or respiratory rate measurements by means of radar technology was analyzed. In 37% of the included studies on the measurement of the respiratory rate and in 48% of those on the measurement of the heart rate, the maximum deviation was 5%. For a tolerated deviation of 10%, the corresponding percentages were 85% and 87%, respectively. However, the quantitative comparability of the results available in the current literature is very limited due to a variety of variables. The elimination of the problem of confounding variables and the continuation of the tendency to focus on the algorithm applied will continue to constitute a central topic of radar-based vital parameter measurement. Promising fields of application of research can be found in particular in areas that require non-contact measurements. This includes infection events, emergency medicine, disaster situations and major catastrophic incidents.
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Affiliation(s)
- Magdalena Liebetruth
- German Air Force Centre of Aerospace Medicine, 51147 Cologne, Germany
- Department of Occupational Medicine, Faculty of Medicine, Otto von Guericke University of Magdeburg, 39120 Magdeburg, Germany
| | - Kai Kehe
- Bundeswehr Medical Service Headquarter, Department A-VI Public Health, 56072 Koblenz, Germany
| | - Dirk Steinritz
- Bundeswehr Institute of Pharmacology and Toxicology, 80937 Munich, Germany
| | - Stefan Sammito
- German Air Force Centre of Aerospace Medicine, 51147 Cologne, Germany
- Department of Occupational Medicine, Faculty of Medicine, Otto von Guericke University of Magdeburg, 39120 Magdeburg, Germany
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2
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Truong T, Kim J. A Wearable Strain Sensor Utilizing Shape Memory Polymer/Carbon Nanotube Composites Measuring Respiration Movements. Polymers (Basel) 2024; 16:373. [PMID: 38337262 DOI: 10.3390/polym16030373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 01/18/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024] Open
Abstract
Flexible wearable sensors are integral in diverse applications, particularly in healthcare and human-computer interaction systems. This paper introduces a resistive stretch sensor crafted from shape memory polymers (SMP) blended with carbon nanotubes (CNTs) and coated with silver paste. Initially, the sensor's characteristics underwent evaluation using a Universal Testing Machine (UTM) and an LCR meter. These sensors showcased exceptional sensitivity, boasting a gauge factor of up to 20 at 5% strain, making them adept at detecting subtle movements or stimuli. Subsequently, the study conducted a comparison between SMP-CNT conductors with and without the silver coating layer. The durability of the sensors was validated through 1000 cycles of stretching at 4% ∆R/R0. Lastly, the sensors were utilized for monitoring respiration and measuring human breathing. Fourier transform and power spectrum density (PSD) analysis were employed to discern frequency components. Positioned between the chest and abdominal wall for contact-based respiration monitoring, the sensors revealed a dominant frequency of approximately 0.35 Hz. Signal filtering further enhanced their ability to capture respiration signals, establishing them as valuable tools for next-generation personalized healthcare applications.
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Affiliation(s)
- TranThuyNga Truong
- Department of Smart Wearables Engineering, Soongsil University, Seoul 156-743, Republic of Korea
| | - Jooyong Kim
- Department of Materials Science and Engineering, Soongsil University, Seoul 156-743, Republic of Korea
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3
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Zhang D, Peng Z, Van Pul C, Overeem S, Chen W, Dudink J, Andriessen P, Aarts RM, Long X. Combining Cardiorespiratory Signals and Video-Based Actigraphy for Classifying Preterm Infant Sleep States. CHILDREN (BASEL, SWITZERLAND) 2023; 10:1792. [PMID: 38002883 PMCID: PMC10670397 DOI: 10.3390/children10111792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 10/30/2023] [Accepted: 11/04/2023] [Indexed: 11/26/2023]
Abstract
The classification of sleep state in preterm infants, particularly in distinguishing between active sleep (AS) and quiet sleep (QS), has been investigated using cardiorespiratory information such as electrocardiography (ECG) and respiratory signals. However, accurately differentiating between AS and wake remains challenging; therefore, there is a pressing need to include additional information to further enhance the classification performance. To address the challenge, this study explores the effectiveness of incorporating video-based actigraphy analysis alongside cardiorespiratory signals for classifying the sleep states of preterm infants. The study enrolled eight preterm infants, and a total of 91 features were extracted from ECG, respiratory signals, and video-based actigraphy. By employing an extremely randomized trees (ET) algorithm and leave-one-subject-out cross-validation, a kappa score of 0.33 was achieved for the classification of AS, QS, and wake using cardiorespiratory features only. The kappa score significantly improved to 0.39 when incorporating eight video-based actigraphy features. Furthermore, the classification performance of AS and wake also improved, showing a kappa score increase of 0.21. These suggest that combining video-based actigraphy with cardiorespiratory signals can potentially enhance the performance of sleep-state classification in preterm infants. In addition, we highlighted the distinct strengths and limitations of video-based actigraphy and cardiorespiratory data in classifying specific sleep states.
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Affiliation(s)
- Dandan Zhang
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands; (D.Z.); (Z.P.); (C.V.P.); (S.O.); (R.M.A.)
- Department of Personal and Preventive Care, Philips Research, 5556 AE Eindhoven, The Netherlands
| | - Zheng Peng
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands; (D.Z.); (Z.P.); (C.V.P.); (S.O.); (R.M.A.)
- Department of Clinical Physics, Máxima Medical Center, 5504 DB Veldhoven, The Netherlands
| | - Carola Van Pul
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands; (D.Z.); (Z.P.); (C.V.P.); (S.O.); (R.M.A.)
- Department of Clinical Physics, Máxima Medical Center, 5504 DB Veldhoven, The Netherlands
| | - Sebastiaan Overeem
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands; (D.Z.); (Z.P.); (C.V.P.); (S.O.); (R.M.A.)
- Sleep Medicine Center, Kempenhaeghe, 5591 VE Heeze, The Netherlands
| | - Wei Chen
- The Center for Intelligent Medical Electronics, School of Information Science and Technology, Fudan University, Shanghai 200433, China;
| | - Jeroen Dudink
- Department of Neonatology, University Medical Center Utrecht, Wilhelmina Children’s Hospital, 3584 EA Utrecht, The Netherlands;
| | - Peter Andriessen
- Department of Neonatology, Máxima Medical Center, 5504 DB Veldhoven, The Netherlands;
| | - Ronald M. Aarts
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands; (D.Z.); (Z.P.); (C.V.P.); (S.O.); (R.M.A.)
| | - Xi Long
- Department of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands; (D.Z.); (Z.P.); (C.V.P.); (S.O.); (R.M.A.)
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Sacco G, Mercuri M, Hornung R, Visser H, Lorato I, Pisa S, Dolmans G. A SISO FMCW radar based on inherently frequency scanning antennas for 2-D indoor tracking of multiple subjects. Sci Rep 2023; 13:16701. [PMID: 37794080 PMCID: PMC10551012 DOI: 10.1038/s41598-023-41541-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 08/28/2023] [Indexed: 10/06/2023] Open
Abstract
The contextual non-invasive monitoring and tracking of multiple human targets for health and surveillance purposes is an increasingly investigated application. Radars are good candidates, since they are able to remotely monitor people without raising privacy concerns. However, radar systems are typically based on complex architectures involving multiple channels and antennas, such as multiple-input and multiple-output (MIMO) or electronic beam scanning, resulting also in a high power consumption. In contrast with existing technologies, this paper proposes a single-input and single-output (SISO) frequency-modulated continuous wave (FMCW) radar in combination with frequency scanning antennas for tracking multiple subjects in indoor environments. A data processing method is also presented for angular separation and clutter removal. The system was successfully tested in five realistic indoor scenarios involving paired subjects, which were either static or moving along predefined paths varying their range and angular position. In all scenarios, the radar was able to track the targets, reporting a maximum mean absolute error (MAE) of 20 cm and 5.64[Formula: see text] in range and angle, respectively. Practical applications arise for ambient assisted living, telemedicine, smart building applications and surveillance.
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Affiliation(s)
- Giulia Sacco
- Institut d'Électronique et des Technologies du numéRique (IETR), University of Rennes, UMR CNRS 6164, 35000, Rennes, France.
| | - Marco Mercuri
- Dipartimento di Informatica, Modellistica, Elettronica e Sistemistica (DIMES), University of Calabria, 87036, Rende, CS, Italy
| | | | - Huib Visser
- imec-Netherlands, 5656 AE, Eindhoven, The Netherlands
| | - Ilde Lorato
- imec-Netherlands, 5656 AE, Eindhoven, The Netherlands
| | - Stefano Pisa
- Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00184, Rome, Italy
| | - Guido Dolmans
- imec-Netherlands, 5656 AE, Eindhoven, The Netherlands
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Peng Z, Kommers D, Liang RH, Long X, Cottaar W, Niemarkt H, Andriessen P, van Pul C. Continuous sensing and quantification of body motion in infants: A systematic review. Heliyon 2023; 9:e18234. [PMID: 37501976 PMCID: PMC10368857 DOI: 10.1016/j.heliyon.2023.e18234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 06/26/2023] [Accepted: 07/12/2023] [Indexed: 07/29/2023] Open
Abstract
Abnormal body motion in infants may be associated with neurodevelopmental delay or critical illness. In contrast to continuous patient monitoring of the basic vitals, the body motion of infants is only determined by discrete periodic clinical observations of caregivers, leaving the infants unattended for observation for a longer time. One step to fill this gap is to introduce and compare different sensing technologies that are suitable for continuous infant body motion quantification. Therefore, we conducted this systematic review for infant body motion quantification based on the PRISMA method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). In this systematic review, we introduce and compare several sensing technologies with motion quantification in different clinical applications. We discuss the pros and cons of each sensing technology for motion quantification. Additionally, we highlight the clinical value and prospects of infant motion monitoring. Finally, we provide suggestions with specific needs in clinical practice, which can be referred by clinical users for their implementation. Our findings suggest that motion quantification can improve the performance of vital sign monitoring, and can provide clinical value to the diagnosis of complications in infants.
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Affiliation(s)
- Zheng Peng
- Department of Applied Physics, Eindhoven University of Technology, Eindhoven, the Netherlands
- Department of Clinical Physics, Máxima Medical Centre, Veldhoven, the Netherlands
| | - Deedee Kommers
- Department of Applied Physics, Eindhoven University of Technology, Eindhoven, the Netherlands
- Department of Neonatology, Máxima Medical Centre, Veldhoven, the Netherlands
| | - Rong-Hao Liang
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
- Department of Industrial Design, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Xi Long
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
- Philips Research, Eindhoven, the Netherlands
| | - Ward Cottaar
- Department of Applied Physics, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Hendrik Niemarkt
- Department of Applied Physics, Eindhoven University of Technology, Eindhoven, the Netherlands
- Department of Neonatology, Máxima Medical Centre, Veldhoven, the Netherlands
| | - Peter Andriessen
- Department of Applied Physics, Eindhoven University of Technology, Eindhoven, the Netherlands
- Department of Neonatology, Máxima Medical Centre, Veldhoven, the Netherlands
| | - Carola van Pul
- Department of Applied Physics, Eindhoven University of Technology, Eindhoven, the Netherlands
- Department of Clinical Physics, Máxima Medical Centre, Veldhoven, the Netherlands
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Kundu S, Panda G, Routray A, Guha R, Mohanty P. Contactless Monitoring Of Human Vitals: A Study With Simultaneous Measurements Using FMCW Radar And Thermal Camera. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38082922 DOI: 10.1109/embc40787.2023.10340754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
This paper proposes contactless monitoring of Heart Rate (HR) and Breath Rate (BR) with simultaneous measurements using Frequency Modulated Continuous Wave (FMCW) radar and thermal camera. The radar collects the body movement signals which include Random Body Movements (RBMs). Non-negative Matrix Factorization (NMF) and Wavelet analysis were used on this signal to get the accurate values of HR and BR. Similarly, with thermal imaging, nostril and forehead regions are tracked to estimate the values of BR as well as HR. We conducted an experiment with 50 subjects to find similarities in the performance of radar and thermal camera while measuring HR and BR. Simultaneously, these two methods have been validated with pulse oximeter and visual camera. From the visual camera, we can get the abdominal movements on which the BR can be ascertained whereas pulse oximeter gives us the HR. Radar signals are degraded because of large RBMs whereas thermal signals get distorted because of sudden temperature changes in the surroundings, sweating, and occlusion. We used a Signal Quality Metric (SQM) to ascertain the measurement quality of the vital signs. This SQM-based approach can further be used for sensor fusion to build a robust contactless system to monitor vital signs.Clinical relevance- Contactless and accurate measurement of HR and BR is very essential for continuous and comfortable monitoring of vitals. In this paper, we combine both FMCW radar and thermal camera so that one can complement the other in adverse scenarios on the basis of signal quality.
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Boiko A, Martínez Madrid N, Seepold R. Contactless Technologies, Sensors, and Systems for Cardiac and Respiratory Measurement during Sleep: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23115038. [PMID: 37299762 DOI: 10.3390/s23115038] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023]
Abstract
Sleep is essential to physical and mental health. However, the traditional approach to sleep analysis-polysomnography (PSG)-is intrusive and expensive. Therefore, there is great interest in the development of non-contact, non-invasive, and non-intrusive sleep monitoring systems and technologies that can reliably and accurately measure cardiorespiratory parameters with minimal impact on the patient. This has led to the development of other relevant approaches, which are characterised, for example, by the fact that they allow greater freedom of movement and do not require direct contact with the body, i.e., they are non-contact. This systematic review discusses the relevant methods and technologies for non-contact monitoring of cardiorespiratory activity during sleep. Taking into account the current state of the art in non-intrusive technologies, we can identify the methods of non-intrusive monitoring of cardiac and respiratory activity, the technologies and types of sensors used, and the possible physiological parameters available for analysis. To do this, we conducted a literature review and summarised current research on the use of non-contact technologies for non-intrusive monitoring of cardiac and respiratory activity. The inclusion and exclusion criteria for the selection of publications were established prior to the start of the search. Publications were assessed using one main question and several specific questions. We obtained 3774 unique articles from four literature databases (Web of Science, IEEE Xplore, PubMed, and Scopus) and checked them for relevance, resulting in 54 articles that were analysed in a structured way using terminology. The result was 15 different types of sensors and devices (e.g., radar, temperature sensors, motion sensors, cameras) that can be installed in hospital wards and departments or in the environment. The ability to detect heart rate, respiratory rate, and sleep disorders such as apnoea was among the characteristics examined to investigate the overall effectiveness of the systems and technologies considered for cardiorespiratory monitoring. In addition, the advantages and disadvantages of the considered systems and technologies were identified by answering the identified research questions. The results obtained allow us to determine the current trends and the vector of development of medical technologies in sleep medicine for future researchers and research.
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Affiliation(s)
- Andrei Boiko
- Ubiquitous Computing Laboratory, Department of Computer Science, HTWG Konstanz-University of Applied Sciences, Alfred-Wachtel-Str. 8, 78462 Konstanz, Germany
| | - Natividad Martínez Madrid
- Internet of Things Laboratory, School of Informatics, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany
| | - Ralf Seepold
- Ubiquitous Computing Laboratory, Department of Computer Science, HTWG Konstanz-University of Applied Sciences, Alfred-Wachtel-Str. 8, 78462 Konstanz, Germany
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8
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Wertheim D, Seddon P. Measuring respiratory rate in children. Acta Paediatr 2023; 112:342-343. [PMID: 36605003 DOI: 10.1111/apa.16645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 12/22/2022] [Indexed: 01/07/2023]
Affiliation(s)
- David Wertheim
- Faculty of Engineering, Computing and the Environment, Kingston University, Surrey, UK
| | - Paul Seddon
- Respiratory Care, Royal Alexandra Children's Hospital, University Hospitals Sussex NHS Foundation Trust, Brighton, UK
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Lim S, Jang GS, Song W, Kim BH, Kim DH. Non-Contact VITAL Signs Monitoring of a Patient Lying on Surgical Bed Using Beamforming FMCW Radar. SENSORS (BASEL, SWITZERLAND) 2022; 22:8167. [PMID: 36365862 PMCID: PMC9656893 DOI: 10.3390/s22218167] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/17/2022] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
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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Affiliation(s)
| | | | | | | | - Dong Hyun Kim
- SMG-SNU Boramae Medical Center, 20, Boramae-ro 5-gil, Dongjak-gu, Seoul 07061, Korea
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Mercuri M, Russo P, Glassee M, Castro ID, De Greef E, Rykunov M, Bauduin M, Bourdoux A, Ocket I, Crupi F, Torfs T. Automatic radar-based 2-D localization exploiting vital signs signatures. Sci Rep 2022; 12:7651. [PMID: 35538128 PMCID: PMC9090773 DOI: 10.1038/s41598-022-11671-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 04/22/2022] [Indexed: 11/23/2022] Open
Abstract
In light of the continuously and rapidly growing senior and geriatric population, the research of new technologies enabling long-term remote patient monitoring plays an important role. For this purpose, we propose a single-input-multiple-output (SIMO) frequency-modulated continuous wave (FMCW) radar system and a signal processing technique to automatically detect the number and the 2-D position (azimuth and range information) of stationary people (seated/lying down). This is achieved by extracting the vital signs signatures of each single individual, separating the Doppler shifts caused by the cardiopulmonary activities from the unwanted reflected signals from static reflectors and multipaths. We then determine the number of human subjects present in the monitored environment by counting the number of extracted vital signs signatures while the 2-D localization is performed by measuring the distance from the radar where the vital signs information is sensed (i.e., locating the thoracic region). We reported maximum mean absolute errors (MAEs) of 0.1 m and 2.29\documentclass[12pt]{minimal}
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\begin{document}$$^{\circ }$$\end{document}∘ in measuring respectively the ranges and azimuth angles. The experimental validation demonstrated the ability of the proposed approach in monitoring paired human subjects in a typical office environment.
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Affiliation(s)
- Marco Mercuri
- DIMES, University of Calabria, 87036, Rende, CS, Italy.
| | - Pietro Russo
- IMEC-Netherlands, 5656 AE, Eindhoven, The Netherlands
| | | | | | | | | | | | | | | | - Felice Crupi
- DIMES, University of Calabria, 87036, Rende, CS, Italy
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