Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Recent Patents on Electrical & Electronic Engineering (Formerly Recent Patents on Electrical Engineering)
  4. Volume 18, Issue 1
  5. Article
Volume 18, Issue 1
  • ISSN: 2213-1116
  • E-ISSN: 2213-1132

Abstract

COVID-19 (Corona Virus Disease of 2019) is a global pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) virus. This disease has significantly impacted every aspect of people's lives, including their work style, leisure activities, and use of technology. Additionally, due to psychological factors or other reasons, there has been a surge in deaths from cardiovascular failure during the pandemic. As COVID-19 is a silent killer whose symptoms only become visible after significant damage has been done, constant monitoring of heart parameters is crucial to address this issue. This paper explores the emerging trends in monitoring vital signs such as the electrocardiogram (ECG), heart rate, respiration rate (breaths), related sensors, remote sensor organization, and telemedicine innovations. Furthermore, this paper discusses the potential application of non-contact radar-based remote monitoring for vital sign monitoring of affected patients.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/eeng/10.2174/0123520965257847231108075618
2025-01-01
2024-12-26

  • From This Site

    /content/journals/eeng/10.2174/0123520965257847231108075618
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. GhebreyesusT. A. World Health OrganizationWHO Director- General’s opening remarks at the media briefing on COVID-19-25.2020
     [Google Scholar]
  2. VoraK.S. SaiyedS. NatesanS. Impact of COVID-19 on family planning services in India.Sex. Reprod. Health Matters2020281178537810.1080/26410397.2020.1785378 32552622
     [Google Scholar]
  3. AkinbiA. ForshawM. BlinkhornV. Contact tracing apps for the COVID-19 pandemic: A systematic literature review of challenges and future directions for neo-liberal societies.Health Inf. Sci. Syst.2021911810.1007/s13755‑021‑00147‑7 33868671
     [Google Scholar]
  4. World Health Organization World Health Organization,COVID-19 immunization in refugees and migrants: principles and key considerations: interim guidance.2021
     [Google Scholar]
  5. LinQ. SongS. CastroI.D. JiangH. KonijnenburgM. van WegbergR. BiswasD. StanzioneS. SijbersW. Van HoofC. TavernierF. Van HelleputteN. Wearable multiple modality bio-signals recording and processing on chip: A review.IEEE Sens. J.20212121108112310.1109/JSEN.2020.3016115
     [Google Scholar]
  6. VanN.T.P. TangL. SinghA. MinhN.D. MukhopadhyayS.C. HasanS.F. Self-identification respiratory disorder based on con-tinuous wave radar sensor system.IEEE Access20197400194002610.1109/ACCESS.2019.2906885
     [Google Scholar]
  7. WangP. MaY. LiangF. ZhangY. YuX. LiZ. AnQ. LvH. WangJ. Non-contact vital signs monitoring of dog and cat using UWB radar.Animals202010220510.3390/ani10020205 31991803
     [Google Scholar]
  8. MassaroniC. NicoloA. SacchettiM. SchenaE. Contactless methods for measuring respiratory rate: A review.IEEE Sens. J.20212111128211283910.1109/JSEN.2020.3023486
     [Google Scholar]
  9. ErnstR. Vital Sign Radar: Development of a compact, highly integrated 60GHz FMCW Radar for Human Vital Sign Monitoring.Halmstad University, School of Information Technology2016
     [Google Scholar]
  10. UysalC. FilikT. RF-based noncontact respiratory rate monitoring with parametric spectral estimation.IEEE Sens. J.201919219841984910.1109/JSEN.2019.2927536
     [Google Scholar]
  11. AhmadA. RohJ.C. WangD. DubeyA. "Vital signs monitoring of multiple people using a FMCW millimetre-wave sensor", 2018 IEEE Radar Conference20181450145510.1109/RADAR.2018.8378778
     [Google Scholar]
  12. ChenY. Pervasive sensing.Smart Assisted Living. Computer Communications and Networks. ChenF. García-BetancesR. ChenL. Cabrera-UmpiérrezM. NugentC. ChamSpringer202010.1007/978‑3‑030‑25590‑9_1
     [Google Scholar]
  13. LiuJ. LiuH. ChenY. WangY. WangC. Wireless sensing for human activity: A survey.IEEE Commun. Surv. Tutor.20202231629164510.1109/COMST.2019.2934489
     [Google Scholar]
  14. KumariT. KumariR. DeviN. SharmaB. "Personalized healthcare monitoring system", In 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)20211088109610.1109/ICOEI51242.2021.9453056
     [Google Scholar]
  15. AbuellaH. EkinS. Non-contact vital signs monitoring through visible light sensing.IEEE Sens. J.20202073859387010.1109/JSEN.2019.2960194
     [Google Scholar]
  16. YangX. SunG. IshibashiK. Non-contact acquisition of respiration and heart rates using Doppler radar with time domain peak-detection algorithmIn 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)20172847285010.1109/EMBC.2017.8037450
     [Google Scholar]
  17. MerinO. AshN. LevyG. SchwaberM.J. KreissY. The Israeli field hospital in Haiti--ethical dilemmas in early disaster re-sponse.N. Engl. J. Med.201036211e3810.1056/NEJMp1001693 20200362
     [Google Scholar]
  18. ChauhanS.S. BasuA. AbegaonkarM.P. KoulS.K. Through the wall human subject localization and respiration rate detection us-ing multichannel Doppler radar.IEEE Sens. J.202021215101518
     [Google Scholar]
  19. ChangC.M. HungC.C. ZhaoC. LinC.L. HsuB.Y. "Learning-based Remote Photoplethysmography for Physiological Signal Feed-back Control in Fitness Training", 15th IEEE Conference on Industrial Electronics and Applications (ICIEA)202010.1109/ICIEA48937.2020.9248164
     [Google Scholar]
  20. JiangZ. HuM. GaoZ. FanL. DaiR. PanY. TangW. ZhaiG. LuY. Detection of respiratory infections using RGB-infrared sensors on portable device.IEEE Sens. J.20202022136741368110.1109/JSEN.2020.3004568
     [Google Scholar]
  21. CetinkayaN. TurhanS. PinarerO. Respiratory rate prediction algorithm based on pulse oximeter IEEE International Confer-ence on Big Data.Orlando, FL, USABig Data20214652465810.1109/BigData52589.2021.9671288
     [Google Scholar]
  22. VadrevuS. ManikandanM.S. Real-Time quality-Aware ppg waveform delineation and parameter extraction for effective unsuper-vised and iot health monitoring systems.IEEE Sens. J.201919177613762310.1109/JSEN.2019.2917157
     [Google Scholar]
  23. GhodratigoharM. GhanadianH. Al OsmanH. A remote respiration rate measurement method for non-stationary subjects using CEEMDAN and machine learning.IEEE Sens. J.20202031400141010.1109/JSEN.2019.2946132
     [Google Scholar]
  24. JainM. DebS. SubramanyamA.V. Face video based touchless blood pressure and heart rate estimationIEEE 18th International Workshop on Multimedia Signal Processing (MMSP).Montreal, QC, Canada,20161510.1109/MMSP.2016.7813389
     [Google Scholar]
  25. UenoyamaM. MatsuiT. YamadaK. SuzukiS. TakaseB. SuzukiS. IshiharaM. KawakamiM. Non-contact respiratory monitor-ing system using a ceiling-attached microwave antenna.Med. Biol. Eng. Comput.200644983584010.1007/s11517‑006‑0091‑8 16941101
     [Google Scholar]
  26. ChenX. ChengJ. SongR. LiuY. WardR. WangZ.J. Video-based heart rate measurement: Recent advances and future pro-spects.IEEE Trans. Instrum. Meas.201968103600361510.1109/TIM.2018.2879706
     [Google Scholar]
  27. ReynoldsB.B. PatrieJ. HenryE.J. GoodkinH.P. BroshekD.K. WintermarkM. DruzgalT.J. Comparative analysis of head impact in contact and collision sports.J. Neurotrauma2017341384910.1089/neu.2015.4308 27541183
     [Google Scholar]
  28. SahooS.S. MohantyS. MajhiB. A secure three factor based authentication scheme for health care systems using IoT enabled de-vices.J. Ambient Intell. Humaniz. Comput.20211211419143410.1007/s12652‑020‑02213‑6
     [Google Scholar]
  29. RoyS. SarkarD. DeD. Entropy-aware ambient IoT analytics on humanized music information fusion.J. Ambient Intell. Humaniz. Comput.202011115117110.1007/s12652‑019‑01261‑x
     [Google Scholar]
  30. BansalM. GandhiB. IoT & big data in smart healthcare (ECG monitoringInternational Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon)Faridabad, India390396201910.1109/COMITCon.2019.8862197
     [Google Scholar]
  31. GultepeE. GreenJ.P. NguyenH. AdamsJ. AlbertsonT. TagkopoulosI. From vital signs to clinical outcomes for patients with sepsis: A machine learning basis for a clinical decision support system.J. Am. Med. Inform. Assoc.201421231532510.1136/amiajnl‑2013‑001815 23959843
     [Google Scholar]
  32. UddinM. KhaksarW. TorresenJ. Ambient sensors for elderly care and independent living: A survey.Sensors 2018187202710.3390/s18072027 29941804
     [Google Scholar]
  33. AquevequeP. GermanyE. OsorioR. PasteneF. Gait segmentation method using a plantar pressure measurement system with custom-made capacitive sensors.Sensors202020365610.3390/s20030656 31991637
     [Google Scholar]
  34. EckmanM.H. WiseR. LeonardA.C. DixonE. BurrowsC. KhanF. WarmE. Impact of health literacy on outcomes and effec-tiveness of an educational intervention in patients with chronic diseases.Patient Educ. Couns.201287214315110.1016/j.pec.2011.07.020 21925823
     [Google Scholar]
  35. SindhuraV. RamyaP. YelisettiS. An IOT based smart mobile health monitoring systemSecond International Conference on Inventive Communication and Computational Technologies (ICICCT)Coimbatore, India11861192201810.1109/ICICCT.2018.8473078
     [Google Scholar]
  36. LimT.W. ToombsA. Pose estimation using a flash lidar.Session: Spacecraft Rendezvous and Proximity Operations201410.2514/6.2014‑0089
     [Google Scholar]
  37. UysalC. FilikT. MUSIC algorithm for respiratory rate estimation using RF signals.Electrica201818230030910.26650/electrica.2018.03405
     [Google Scholar]
  38. KhezrS. MoniruzzamanM. YassineA. BenlamriR. Blockchain technology in healthcare: A comprehensive review and directions for future research.Appl. Sci.201999173610.3390/app9091736
     [Google Scholar]
  39. SinhalR. SinghK. RaghuwanshiM.M. "An overview of remote photoplethysmography methods for vital sign monitoring", International Symposium,ISCMM 2019213110.1007/978‑981‑13‑8798‑2_3
     [Google Scholar]
  40. Bin ObadiA. SohP.J. AldayelO. Al-DooriM.H. MercuriM. SchreursD. A survey on vital signs detection using radar tech-niques and processing with FPGA implementation.IEEE Circuits Syst. Mag.2021211417410.1109/MCAS.2020.3027445
     [Google Scholar]
  41. LuY. XuL.D. Internet of Things (IoT) cybersecurity research: A review of current research topics.IEEE Internet Things J.2019622103211510.1109/JIOT.2018.2869847
     [Google Scholar]
  42. MassaoudiM. Abu-RubH. RefaatS.S. ChihiI. OueslatiF.S. Deep learning in smart grid technology: A review of recent advance-ments and future prospects.IEEE Access20219545585457810.1109/ACCESS.2021.3071269
     [Google Scholar]
  43. YinX. WuG. WeiJ. ShenY. QiH. YinB. Deep learning on traffic prediction: Methods, analysis, and future directions.IEEE Trans. Intell. Transp. Syst.20222364927494310.1109/TITS.2021.3054840
     [Google Scholar]
  44. DavisC.M. Gait and Cognition: Exploring Cognition and Dual-task Costs in a Group of Community Dwelling Alzheimer’s Disease Pa-tients over 6 Months.Graduate Studies and Research2022
     [Google Scholar]
  45. RafeeqM. AlamS. "Automation of plastic, metal and glass waste materials segregation using arduino in scrap industry", 2016 Inter-national Conference on Communication and Electronics Systems (ICCES)20161510.1109/CESYS.2016.7889840
     [Google Scholar]
  46. M. hen, Y. Ma, J. Song, C.F. Lai, and B. Hu, “Smart clothing: Connecting human with clouds and big data for sustainable health monitor-ing”.Mob. Netw. Appl.201621825845
     [Google Scholar]
  47. LiguoriC. RomigiA. NuccetelliM. ZanninoS. SancesarioG. MartoranaA. AlbaneseM. MercuriN.B. IzziF. BernardiniS. NittiA. SancesarioG.M. SicaF. MarcianiM.G. PlacidiF. Orexinergic system dysregulation, sleep impairment, and cognitive decline in Alzheimer disease.JAMA Neurol.201471121498150510.1001/jamaneurol.2014.2510 25322206
     [Google Scholar]
  48. KohaneI.S. McMurryA. WeberG. MacFaddenD. RappaportL. KunkelL. BickelJ. WattanasinN. SpenceS. MurphyS. ChurchillS. The co-morbidity burden of children and young adults with autism spectrum disorders.PLoS One201274e3322410.1371/journal.pone.0033224 22511918
     [Google Scholar]
  49. WuO. CloonanL. MockingS.J.T. BoutsM.J.R.J. CopenW.A. Cougo-PintoP.T. FitzpatrickK. KanakisA. SchaeferP.W. RosandJ. FurieK.L. RostN.S. Role of acute lesion topography in initial ischemic stroke severity and long-term functional outcomes.Stroke20154692438244410.1161/STROKEAHA.115.009643 26199314
     [Google Scholar]
  50. GaravanT.N. McCarthyA. CarberyR. An ecosystems perspective on international human resource development: A meta-synthesis of the literature.Hum. Resour. Dev. Rev.201918224828810.1177/1534484319828865
     [Google Scholar]
  51. ZhangN. WangM. WuB. HanM. YinB. CaoJ. WangC. Temperature-insensitive magnetic field sensor based on an optoelec-tronic oscillator merging a Mach–Zehnder interferometer.IEEE Sens. J.202020137053705910.1109/JSEN.2020.2973515
     [Google Scholar]
  52. CarvalhoP.M. FelícioM.R. SantosN.C. GonçalvesS. DominguesM.M. Application of light scattering techniques to nanoparticle characterization and development.Front Chem.2018623710.3389/fchem.2018.00237 29988578
     [Google Scholar]
  53. DuanZ. JiangY. HuangQ. YuanZ. ZhaoQ. WangS. ZhangY. TaiH. A do-it-yourself approach to achieving a flexible pres-sure sensor using daily use materials.J. Mater. Chem. C Mater. Opt. Electron. Devices2021939136591366710.1039/D1TC03102C
     [Google Scholar]
  54. ParkY.J. FanS.K.S. HsuC.Y. A review on fault detection and process diagnostics in industrial processes.Processes202089112310.3390/pr8091123
     [Google Scholar]
  55. OkeduK.E. BarghashH. Enhancing the transient state performance of permanent magnet synchronous generator based variable speed wind turbines using power converters excitation parameters.Front. Energy Res.2021965505110.3389/fenrg.2021.655051
     [Google Scholar]
  56. BoopathiD. JagatheesanK. AnandB. KumarakrishnanV. SamantaS. Effect of sustainable energy sources for load frequency control (LFC) of single-area wind power systems.Industrial Transformation.CRC Press20228798
     [Google Scholar]
  57. BaggaS. SharmaD.K. SinghK.K. SinghA. Clustering based routing protocol for wireless sensor networks using the concept of zonal division of network field.J. Signal Process. Syst. Signal Image Video Technol.2022113
     [Google Scholar]
  58. DurmazU. YalcinkayaO. Experimental investigation on the ground heat exchanger with air fluid.Int. J. Environ. Sci. Technol.20191695213521810.1007/s13762‑019‑02205‑w
     [Google Scholar]
  59. LiX. ZhangD. Coordinated control and energy management strategies for hundred megawatt-level battery energy storage stations based on multi-agent theory2018 International Conference on Advanced Mechatronic Systems (ICAMechS)20181510.1109/ICAMechS.2018.8506868
     [Google Scholar]
  60. YangS.W. HyonY.K. NaH.S. JinL. LeeJ.G. ParkJ.M. LeeJ.Y. ShinJ.H. LimJ.S. NaY.G. JeonK. HaT. KimJ. SongK.H. Machine learning prediction of stone-free success in patients with urinary stone after treatment of shock wave lithotripsy.BMC Urol.20202018810.1186/s12894‑020‑00662‑x 32620102
     [Google Scholar]
  61. WangH. ZhouY. PengY. LiuH. QinJ. Predicting the impact of network topology on synchronization using machine learning.IEEE Trans. Neural Netw. Learn. Syst.202031618261836
     [Google Scholar]
  62. LamC.W. ZhangX. WongK.K. Data-driven machine learning in credit risk modelling.Expert Syst. Appl.2019135246259
     [Google Scholar]
  63. MousaviS.M. GhasemiM. JahromiM.Z. A comparative study of machine learning algorithms for predicting student’s academic performance.J. Comput. High. Educ.2018302389406
     [Google Scholar]
  64. SarkarA. SinghA.K. ShuklaA.K. TiwariM.K. Performance evaluation of soft computing techniques for prediction of wind ener-gy potential: A review.J. Clean. Prod.2021279123520
     [Google Scholar]
  65. WangJ. YuanY. YangX. WangS. LiuY. A comprehensive review on smart home energy management systems.J. Clean. Prod.2019229552565
     [Google Scholar]
  66. JevremovicN. MitovV. "IoT Smart Farming Solutions", 2020 IEEE 27th International Conference on Electronics, Circuits and Systems (ICECS)2020
     [Google Scholar]
  67. SaeedM. LieuD. "A review on blockchain technology and its applications", 2020 IEEE International Conference on Information and Communication Technologies for Disaster Management (ICTDM)202016
     [Google Scholar]
  68. ChenW. Heart rate monitoring: A comprehensive review.J. Med. Biol. Eng.201939111410.1007/s40846‑017‑0296‑3
     [Google Scholar]
  69. JavorkovaL. "Prediction of neonatal respiratory distress syndrome by placental alpha microglobulin-1 and creatinine", 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)2020
     [Google Scholar]
  70. MaX. "A comprehensive study on lossy compression for deep neural networks", 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)202117321736
     [Google Scholar]
  71. ZhangM. DuanZ. ZhangB. YuanZ. ZhaoQ. JiangY. TaiH. Electrochemical humidity sensor enabled self-powered wireless humidity detection system.Nano Energy202311510874510.1016/j.nanoen.2023.108745
     [Google Scholar]
  72. RaghuramS. "A review of vehicle-to-vehicle communication protocols and technologies for autonomous cars", 2020 International Con-ference on Advances in Computing, Communication Control and Networking.ICACCCN2020386391
     [Google Scholar]
  73. ShahR. SchumannJ. "Design of a smart irrigation system using IoT and machine learning", 2019 IEEE International Conference on Electro Information Technology (EIT)2019154159
     [Google Scholar]
  74. ZhaoW. A review on graph neural networks: Models, applications, and challenges.IEEE Trans. Neural Netw. Learn. Syst.202132412391265
     [Google Scholar]
  75. BarbéF. RoquillyA. LoutrelO. AsehnouneK. Monitoring hemodynamic parameters.Best Pract. Res. Clin. Anaesthesiol.2020342355367
     [Google Scholar]
  76. MokhlesiB. LearyE.B. MurrayP. Monitoring vital signs in the intensive care unit.Am. J. Respir. Crit. Care Med.202120311P2 32791002
     [Google Scholar]
  77. KohW. ChakravarthyM. SimonE. RasiahR. CharuluxanananS. KimT.Y. ChewS.T.H. BräuerA. TiL.K. Perioperative tem-perature management: A survey of 6 Asia–Pacific countries.BMC Anesthesiol.202121120510.1186/s12871‑021‑01414‑6 34399681
     [Google Scholar]
  78. PfütznerA. LübbenG. DahlA. Continuous glucose monitoring: current and future applications.Lancet Diabetes Endocrinol.202198479488
     [Google Scholar]
  79. ChauhanA. YasinM.A. RoyP.P. BhattacharyaP. "Photoplethysmography signal processing techniques for heart rate variability analysis", 2018 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES)2018369373
     [Google Scholar]
  80. FonsecaP. CarvalhoP. FerreiraJ. CardosoJ. PostolacheO. Wearable medical device for remote monitoring of COVID-19 pa-tients.IEEE J. Biomed. Health Inform.2020241235353541
     [Google Scholar]
  81. BocciaG. CarotenutoR. MaffeiL. GiordanoA. GuarinoA. A wearable device for sleep apnoea syndrome diagnosis based on respiratory sound analysis.IEEE Trans. Instrum. Meas.201665612961306
     [Google Scholar]
  82. KumarM. ChandwaniR. KumarV. "An improved approach for QRS detection in ECG signal", 2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE)", 2015410415
     [Google Scholar]
  83. MahmoudS.M. MohamedE.A. MansourH.M. An enhanced QRS complex detection method using double-threshold based on ECG signal energy.J. Med. Syst.201741585 28401396
     [Google Scholar]
  84. AydinE. DurmusY.Y. KalyoncuM. A machine learning approach for detection of hypertension using photoplethysmography signal.Measurement2019139248253
     [Google Scholar]
  85. KimT.Y. LeeH.J. ChoC.H. KimK.K. Performance evaluation of a wearable respiratory monitoring system for real-time respira-tory rate measurement during exercise.J. Med. Syst.201842610610.1007/s10916‑018‑0929‑2 29700626
     [Google Scholar]
  86. HafezM.M. KamelM.S. Automated sleep stage classification using single-channel EEG signals and deep belief networks.J. Neurosci. Methods2021357109154
     [Google Scholar]
  87. HuangN.E. ShenZ. LongS.R. WuM.C. ShihH.H. ZhengQ. LiuH.H. "The empirical mode decomposition and the Hilbert spec-trum for nonlinear and non-stationary time series analysis", Proceedings of the Royal Society A4541998197190399510.1098/rspa.1998.0193
     [Google Scholar]
  88. MallatS. A wavelet tour of signal processing: the sparse way.Academic press1999
     [Google Scholar]
  89. GaoX. ChenH. NieX. YangY. ZhangL. LiuT. WangX. Smartphone-based fall detection with a high accuracy through multi-modal sensory fusion.Nonlinear Dyn.2013731-2871881
     [Google Scholar]
  90. YanJ. HuangH. WeiM. WangT. LiuX. ZhaoY. WeiD. Human gait recognition via 3D feature extraction based on the RGB-D sensor.IEEE Access20219117843117856
     [Google Scholar]
  91. YangD. ZhuZ. LiangB. Vital sign signal extraction method based on permutation entropy and EEMD algorithm for ultra-wideband radar.IEEE Access2019717887917889010.1109/ACCESS.2019.2958600
     [Google Scholar]
  92. HuangM.C. LiuJ.J. XuW. GuC. LiC. SarrafzadehM. A self-calibrating radar sensor system for measuring vital signs.IEEE Trans. Biomed. Circuits Syst.201610235236310.1109/TBCAS.2015.2411732 26011865
     [Google Scholar]
  93. ObeidD. ZahariaG. SadekS. El ZeinG. RateH. Detection vs electrocardiogram.IFMBE Proc.20121126102617
     [Google Scholar]
  94. AdibF. MaoH. KabelacZ. KatabiD. MillerR.C. "Smart homes that monitor breathing and heart rate", Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems201583784610.1145/2702123.2702200
     [Google Scholar]
  95. WangY. WangW. ZhouM. RenA. TianZ. Remote monitoring of human vital signs based on 77-GHZ MM-WAVE FMCW ra-dar.Sensors20202010299910.3390/s20102999 32466309
     [Google Scholar]
  96. DuF. WangH. ZhuH. CaoQ. Vital Sign Signal Extraction Based on mmWave Radar.Journal of Computer and Communications202210314115010.4236/jcc.2022.103009
     [Google Scholar]
  97. RanaS.P. DeyM. BrownR. SiddiquiH.U. DudleyS. "Remote vital sign recognition through machine learning augmented UWB", 2018 IET International Conference on Wireless Sensor Network (IET-WSN 2018)20181610.1049/cp.2018.0978
     [Google Scholar]
  98. WangJ. KarpT. Munoz-FerrerasJ.M. Gomez-GarciaR. LiC. "A spectrum-efficient FSK radar solution for stationary human sub-ject localization based on vital sign signals", 2019 IEEE MTT-S International Microwave Symposium (IMS)201914014310.1109/MWSYM.2019.8700837
     [Google Scholar]
  99. TangM.C. KuoC.Y. WunD.C. WangF.K. HorngT.S. A self- and mutually injection-locked radar system for monitoring vital signs in real time with random body movement cancellation.IEEE Trans. Microw. Theory Tech.201664124812482210.1109/TMTT.2016.2623612
     [Google Scholar]
  100. TangM.C. WangF.K. HorngT.S. "A single radar-based vital sign monitoring system with resistance to large body motion", IEEE MTT-S International Microwave Symposium Digest201799599810.1109/MWSYM.2017.8058758
     [Google Scholar]
  101. JensenB.S. JohansenT.K. YanL. "An experimental vital signs detection radar using low-IF heterodyne architecture and single-sideband transmission", 2013 IEEE International Wireless Symposium (IWS)20131410.1109/IEEE‑IWS.2013.6616752
     [Google Scholar]
  102. SchreursD. MercuriM. SohP.J. VandenboschG. "Radar-based health monitoring", 2013 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications (IMWS-BIO)201313
     [Google Scholar]
  103. XiaoY. LiC. LinJ. A portable noncontact heartbeat and respiration monitoring system using 5-GHz radar.IEEE Sens. J.2007771042104310.1109/JSEN.2007.895979
     [Google Scholar]
  104. MostafanezhadI. YavariE. Boric-LubeckeO. "A low cost simple RF front end using time-domain multiplexing for direction of arrival estimation of physiological signals", IEEE MTT-S International Microwave Symposium Digest2013131610.1109/MWSYM.2013.6697778
     [Google Scholar]
  105. YeC. ToyodaK. OhtsukiT. Blind source separation on non-contact heartbeat detection by non-negative matrix factorization algo-rithms.IEEE Trans. Biomed. Eng.202067248249410.1109/TBME.2019.2915762 31071015
     [Google Scholar]
  106. PintoR. P. KundargiJ. M. Signal processing approach to reduce clutter in RF injection-locked radar.2014
     [Google Scholar]
  107. JiangY. DuanZ. FanZ. YaoP. YuanZ. JiangY. CaoY. TaiH. Power generation humidity sensor based on NaCl/halloysite nanotubes for respiratory patterns monitoring.Sens. Actuators B Chem.202338013339610.1016/j.snb.2023.133396
     [Google Scholar]
  108. ZhaoQ. JiangY. YuanL. YuanZ. ZhangB. LiuB. ZhangM. HuangQ. DuanZ. TaiH. Hydrophilic hyaluronic acid-induced crumpling of Nb2CT nanosheets: Enabling fast humidity sensing based on primary battery.Sens. Actuators B Chem.202339213408210.1016/j.snb.2023.134082
     [Google Scholar]
/content/journals/eeng/10.2174/0123520965257847231108075618
Loading
Comparative Study of Vital Sign Monitoring Techniques and Methods
Recent Patents on Electrical & Electronic Engineering (Formerly Recent Patents on Electrical Engineering) 18, 64; https://doi.org/10.2174/0123520965257847231108075618
/content/journals/eeng/10.2174/0123520965257847231108075618
/content/journals/eeng/10.2174/0123520965257847231108075618
Loading

Data & Media loading...


  • Article Type:     Review Article
Keyword(s): biomedical; cardiorespiratory; continuous wave (CW) doppler radar; corona virus disease of 2019 (COVID-19); electrocardiogram (ECG); healthcare; noncontact monitoring; severe acute respiratory syndrome (SARS); signal processing; Vital signs
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test