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Biomedical Radar and Antenna Systems for Contactless Human Activity Analysis

Part of the Intelligent Systems Reference Library book series (ISRL,volume 207)

Abstract

The elderly population of the world is increasing, and along with that, the need for assisted living and health monitoring. Biomedical radars can be used to monitor the health and safety of patients, both at home and in a clinical setup. This chapter gives a comprehensive overview of biomedical radar and antenna systems for contactless human activity analysis. Recent advancements in this topic are discussed, including original research work for particular applications such as posture recognition, search and rescue, sleep monitoring, activity recognition, identification of individuals, monitoring vital signs, occupancy monitoring, and fall detection. The main challenges and opportunities in this direction are also discussed in detail.

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References

  1. Mercuri, M., Lorato, I.R., Liu, Y.-H., Wieringa, F., Van Hoof, C., Torfs, T.: Vital-sign monitoring and spatial tracking of multiple people using a contactless radar-based sensor. Nat. Electron. 2(6), 252–262 (2019)

    CrossRef  Google Scholar 

  2. Angelov, G.V., Nikolakov, D.P., Ruskova, I.N., Gieva, E.E., Spasova, M.L.: Healthcare sensing and monitoring. In: Enhanced Living Environments, pp. 226–262. Springer (2019)

    Google Scholar 

  3. Ahad, M.A.R., Antar, A.D., Shahid, O.: Vision-based action understanding for assistive healthcare: a short review. In: CVPR Workshops, pp. 1–11 (2019)

    Google Scholar 

  4. Shah, S.A., Fioranelli, F.: RF sensing technologies for assisted daily living in healthcare: a comprehensive review. IEEE Aerosp. Electron. Syst. Mag. 34(11), 26–44 (2019)

    CrossRef  Google Scholar 

  5. Poh, M.-Z., McDuff, D., Picard, R.: A medical mirror for non-contact health monitoring. In: ACM SIGGRAPH 2011 Emerging Technologies, p. 1 (2011)

    Google Scholar 

  6. Hall, T., Lie, D.Y., Nguyen, T.Q., Mayeda, J.C., Lie, P.E., Lopez, J., Banister, R.E.: Non-contact sensor for long-term continuous vital signs monitoring: a review on intelligent phased-array doppler sensor design. Sensors 17(11), 2632 (2017)

    CrossRef  Google Scholar 

  7. Zakrzewski, M.: Methods for doppler radar monitoring of physiological signals (2015)

    Google Scholar 

  8. Chen, V.C., Li, F., Ho, S.-S., Wechsler, H.: Micro-doppler effect in radar: phenomenon, model, and simulation study. IEEE Trans. Aerosp. Electron. Syst. 42(1), 2–21 (2006)

    CrossRef  Google Scholar 

  9. Abdulatif, S., Aziz, F., Altiner, P., Kleiner, B., Schneider, U.: Power-based real-time respiration monitoring using FMCW radar. arXiv preprint arXiv:1711.09198 (2017)

  10. Parker, M.: Digital Signal Processing 101: Everything you need to know to get started. Newnes (2017)

    Google Scholar 

  11. Li, C., Lin, J., Xiao, Y.: Robust overnight monitoring of human vital signs by a non-contact respiration and heartbeat detector. In: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2235–2238. IEEE (2006)

    Google Scholar 

  12. Nosrati, M., Tavassolian, N.: Experimental evaluation of the effects of antenna radiation characteristics on heart rate monitoring radar systems. arXiv preprint arXiv:1801.00484 (2018)

  13. Birsan, N., Munteanu, D.-P., Iubu, G., Niculescu, T.: Time-frequency analysis in doppler radar for noncontact cardiopulmonary monitoring. In: 2011 E-Health and Bioengineering Conference (EHB), pp. 1–4. IEEE (2011)

    Google Scholar 

  14. Tariq, A., Shiraz, H.: Doppler radar vital signs monitoring using wavelet transform. In: 2010 Loughborough Antennas & Propagation Conference, pp. 293–296. IEEE (2010)

    Google Scholar 

  15. Iyer, B., Garg, M., Pathak, N.P., Ghosh, D.: Contactless detection and analysis of human vital signs using concurrent dual-band RF system. Procedia Eng. 64, 185–194 (2013)

    CrossRef  Google Scholar 

  16. Amin, M.G., Zhang, Y.D., Ahmad, F., Ho, K.D.: Radar signal processing for elderly fall detection: the future for in-home monitoring. IEEE Signal Process. Mag. 33(2), 71–80 (2016)

    CrossRef  Google Scholar 

  17. Antar, A.D., Ahmed, M., Ahad, M.A.R.: Challenges in sensor-based human activity recognition and a comparative analysis of benchmark datasets: a review. In: 2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), pp. 134–139. IEEE (2019)

    Google Scholar 

  18. Inui, S., Okusa, K., Maeno, K., Kanakura, T.: Recognizing aspiration presence using model parameter classification from microwave doppler signals. In: 2012 World Congress on Engineering and Computer Science, WCECS 2012, pp. 509–512. Newswood Limited (2012)

    Google Scholar 

  19. Abedi, H., Luo, S., Shaker, G.: On the use of low-cost radars and machine learning for in-vehicle passenger monitoring. In: 2020 IEEE 20th Topical Meeting on Silicon Monolithic Integrated Circuits in RF Systems (SiRF), pp. 63–65. IEEE (2020)

    Google Scholar 

  20. Li, H., Shrestha, A., Heidari, H., Le Kernec, J., Fioranelli, F.: A multisensory approach for remote health monitoring of older people. IEEE J. Electromagnet. RF Microwaves Med. Biol. 2(2), 102–108 (2018)

    CrossRef  Google Scholar 

  21. Kiriazi, J.E., Boric-Lubecke, O., Lubecke, V.M.: Radar cross section of human cardiopulmonary activity for recumbent subject. In: 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4808–4811. IEEE (2009)

    Google Scholar 

  22. Piriyajitakonkij, M., Warin, P., Lakhan, P., Leelaarporn, P., Pianpanit, T., Niparnan, N., Mukhopadhyay, S.C., Wilaiprasitporn, T.: SleepPoseNet: multi-view multi-task learning for sleep postural transition recognition using UWB, arXiv preprint arXiv:2005.02176 (2020)

  23. Cui, H., Dahnoun, N.: Human posture capturing with millimetre wave radars. In: 2020 9th Mediterranean Conference on Embedded Computing (MECO), pp. 1–4. IEEE (2020)

    Google Scholar 

  24. Sengupta, A., Jin, F., Zhang, R., Cao, S.: mm-Pose: real-time human skeletal posture estimation using mmWave radars and CNNs. IEEE Sens. J. (2020)

    Google Scholar 

  25. Ma, B., Chen, B., Zhang, Z., Ma, J., Kong, F.: Combat gesture classification using through-the-wall radar based on multi-domain features association. In: 2020 IEEE Radar Conference (RadarConf20), pp. 1–5. IEEE (2020)

    Google Scholar 

  26. Thi Phuoc Van, N., Tang, L., Demir, V., Hasan, S.F., Duc Minh, N., Mukhopadhyay, S.: Microwave radar sensing systems for search and rescue purposes. Sensors 19(13), 2879 (2019)

    Google Scholar 

  27. Chen, K.-M., Huang, Y., Zhang, J., Norman, A.: Microwave life-detection systems for searching human subjects under earthquake rubble or behind barrier. IEEE Trans. Biomed. Eng. 47(1), 105–114 (2000)

    CrossRef  Google Scholar 

  28. Liu, L., Liu, S.: Remote detection of human vital sign with stepped-frequency continuous wave radar. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 7(3), 775–782 (2014)

    CrossRef  Google Scholar 

  29. Sachs, J., Helbig, M., Herrmann, R., Kmec, M., Schilling, K., Zaikov, E.: Remote vital sign detection for rescue, security, and medical care by ultra-wideband pseudo-noise radar. Ad Hoc Netw. 13, 42–53 (2014)

    CrossRef  Google Scholar 

  30. JalaliBidgoli, F., Moghadami, S., Ardalan, S.: A compact portable microwave life-detection device for finding survivors. IEEE Embed. Syst. Lett. 8(1), 10–13 (2015)

    CrossRef  Google Scholar 

  31. Nakanishi, T., Hirose, A.: Proposal of adaptive search-and-rescue radar system with online complex-valued frequency-domain independent component analysis. In: 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019, pp. 9431–9434. IEEE (2019)

    Google Scholar 

  32. Hu, D., Li, S., Chen, J., Kamat, V.R.: Detecting, locating, and characterizing voids in disaster rubble for search and rescue. Adv. Eng. Inform. 42, 100974 (2019)

    Google Scholar 

  33. Ma, Y., Qi, F., Wang, P., Liang, F., Lv, H., Yu, X., Li, Z., Xue, H., Wang, J., Zhang, Y.: Multiscale residual attention network for distinguishing stationary humans and common animals under through-wall condition using ultra-wideband radar. IEEE Access 8, 121 572–121 583 (2020)

    Google Scholar 

  34. Chen, J., Li, S., Liu, D., Li, X.: AiRobSim: simulating a multisensor aerial robot for urban search and rescue operation and training. Sensors 20(18), 5223 (2020)

    CrossRef  Google Scholar 

  35. Matar, G., Lina, J.-M., Carrier, J., Kaddoum, G.: Unobtrusive sleep monitoring using cardiac, breathing and movements activities: an exhaustive review. IEEE Access 6, 45 129–45 152 (2018)

    Google Scholar 

  36. Tran, V.P., Al-Jumaily, A.A., Islam, S.M.S.: Doppler radar-based non-contact health monitoring for obstructive sleep apnea diagnosis: a comprehensive review. Big Data Cogn. Comput. 3(1), 3 (2019)

    CrossRef  Google Scholar 

  37. Sadek, I., Seet, E., Biswas, J., Abdulrazak, B., Mokhtari, M.: Nonintrusive vital signs monitoring for sleep apnea patients: a preliminary study. IEEE Access 6, 2506–2514 (2017)

    CrossRef  Google Scholar 

  38. Singh, A., Baboli, M., Gao, X., Yavari, E., Padasdao, B., Soll, B., Boric-Lubecke, O., Lubecke, V.: Considerations for integration of a physiological radar monitoring system with gold standard clinical sleep monitoring systems. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 2120–2123. IEEE (2013)

    Google Scholar 

  39. Hong, H., Zhang, L., Zhao, H., Chu, H., Gu, C., Brown, M., Zhu, X., Li, C.: Microwave sensing and sleep: noncontact sleep-monitoring technology with microwave biomedical radar. IEEE Microwave Mag. 20(8), 18–29 (2019)

    CrossRef  Google Scholar 

  40. Lauteslager, T., Kampakis, S., Williams, A.J., Maslik, M., Siddiqui, F.: Performance evaluation of the circadia contactless breathing monitor and sleep analysis algorithm for sleep stage classification. In: 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 5150–5153. IEEE (2020)

    Google Scholar 

  41. Li, X., He, Y., Jing, X.: A survey of deep learning-based human activity recognition in radar. Remote Sens. 11(9), 1068 (2019)

    CrossRef  Google Scholar 

  42. Seyfioğlu, M.S., Serinöz, A., Özbayoğlu, M., Gürbüz, S.Z.: Feature diverse hierarchical classification of human gait with CW radar for assisted living (2017)

    Google Scholar 

  43. Çağlıyan, B., Karabacak, C., Gürbüz, S.Z.: Indoor human activity recognition using bumblebee radar. In: 2014 22nd Signal Processing and Communications Applications Conference (SIU), pp. 1055–1058. IEEE (2014)

    Google Scholar 

  44. Seifert, A.-K., Schäfer, L., Amin, M.G., Zoubir, A.M.: Subspace classification of human gait using radar micro-doppler signatures. In: 2018 26th European Signal Processing Conference (EUSIPCO), pp. 311–315. IEEE (2018)

    Google Scholar 

  45. Jokanović, B., Amin, M.: Fall detection using deep learning in range-doppler radars. IEEE Trans. Aerosp. Electron. Syst. 54(1), 180–189 (2017)

    CrossRef  Google Scholar 

  46. Erol, B., Amin, M.G.: Radar data cube analysis for fall detection. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2446–2450. IEEE (2018)

    Google Scholar 

  47. Li, H., Shrestha, A., Fioranelli, F., Le Kernec, J., Heidari, H., Pepa, M., Cippitelli, E., Gambi, E., Spinsante, S.: Multisensor data fusion for human activities classification and fall detection. In: 2017 IEEE SENSORS, pp. 1–3 . IEEE (2017)

    Google Scholar 

  48. Yang, L., Li, G., Ritchie, M., Fioranelli, F., Griffiths, H.: Gait classification based on micro-doppler features. In: 2016 CIE International Conference on Radar (RADAR), pp. 1–4. IEEE (2016)

    Google Scholar 

  49. Erol, B., Gurbuz, S.Z., Amin, M.G.: GAN-based synthetic radar micro-doppler augmentations for improved human activity recognition. In: 2019 IEEE Radar Conference (RadarConf), pp. 1–5. IEEE (2019)

    Google Scholar 

  50. Islam, S.M.M., Borić-Lubecke, O., Zheng, Y., Lubecke, V.M.: Radar-based non-contact continuous identity authentication. Remote Sens. 12(14), 2279 (2020)

    CrossRef  Google Scholar 

  51. Rahman, A., Yavari, E., Lubecke, V.M., Lubecke, O.-B.: Noncontact doppler radar unique identification system using neural network classifier on life signs. In: 2016 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS), pp. 46–48. IEEE (2016)

    Google Scholar 

  52. Rahman, A., Lubecke, V.M., Boric-Lubecke, O., Prins, J.H., Sakamoto, T.: Doppler radar techniques for accurate respiration characterization and subject identification. IEEE J. Emerg. Sel. Top. Circuits Syst. 8(2), 350–359 (2018)

    CrossRef  Google Scholar 

  53. Islam, S.M., Sylvester, A., Orpilla, G., Lubecke, V.M.: Respiratory feature extraction for radar-based continuous identity authentication. In: 2020 IEEE Radio and Wireless Symposium (RWS), pp. 119–122. IEEE (2020)

    Google Scholar 

  54. Lin, F., Song, C., Zhuang, Y., Xu, W., Li, C., Ren, K.: Cardiac scan: a non-contact and continuous heart-based user authentication system. In: Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking, pp. 315–328 (2017)

    Google Scholar 

  55. Okano, T., Izumi, S., Kawaguchi, H., Yoshimoto, M.: Non-contact biometric identification and authentication using microwave doppler sensor. In: 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), pp. 1–4. IEEE (2017)

    Google Scholar 

  56. Cao, P., Xia, W., Li, Y.: Heart id: human identification based on radar micro-doppler signatures of the heart using deep learning. Remote Sens. 11(10), 1220 (2019)

    CrossRef  Google Scholar 

  57. Huang, M.-C., Liu, J.J., Xu, W., Gu, C., Li, C., Sarrafzadeh, M.: A self-calibrating radar sensor system for measuring vital signs. IEEE Trans. Biomed. Circuits Syst. 10(2), 352–363 (2015)

    CrossRef  Google Scholar 

  58. Zito, D., Pepe, D., Mincica, M., Zito, F., Tognetti, A., Lanata, A., De Rossi, D.: SoC CMOS UWB pulse radar sensor for contactless respiratory rate monitoring. IEEE Trans. Biomed. Circuits Syst. 5(6), 503–510 (2011)

    CrossRef  Google Scholar 

  59. Kuutti, J., Paukkunen, M., Aalto, M., Eskelinen, P., Sepponen, R.E.: Evaluation of a doppler radar sensor system for vital signs detection and activity monitoring in a radio-frequency shielded room. Measurement 68, 135–142 (2015)

    CrossRef  Google Scholar 

  60. Yao, Y., Sun, G., Kirimoto, T., Schiek, M.: Extracting cardiac information from medical radar using locally projective adaptive signal separation. Front. Physiol. 10, 568 (2019)

    CrossRef  Google Scholar 

  61. Cho, H.-S., Park, Y.-J.: Detection of heart rate through a wall using UWB impulse radar. J. Healthcare Eng. 2018 (2018)

    Google Scholar 

  62. Schreurs, D., Mercuri, M., Soh, P.J., Vandenbosch, G.: Radar-based health monitoring. In: 2013 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications (IMWS-BIO), pp. 1–3. IEEE (2013)

    Google Scholar 

  63. Mercuri, M., Schreurs, D., Leroux, P.: SFCW microwave radar for in-door fall detection. In: 2012 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS), pp. 53–56. IEEE (2012)

    Google Scholar 

  64. Adib, F., Kabelac, Z., Katabi, D., Miller, R.C.: 3D tracking via body radio reflections. In: 11th USENIX Symposium on Networked Systems Design and Implementation (NSDI 2014), pp. 317–329 (2014)

    Google Scholar 

  65. Adib, F., Mao, H., Kabelac, Z., Katabi, D., Miller, R.C.: Smart homes that monitor breathing and heart rate. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 837–846 (2015)

    Google Scholar 

  66. Islam, S.M.M.: Can radar remote life sensing technology help to combat Covid-19? (2020)

    Google Scholar 

  67. Barszczyk, A., Lee, K.: Measuring blood pressure: from cuff to smartphone. Curr. Hypertens. Rep. 21(11), 84 (2019)

    CrossRef  Google Scholar 

  68. Luo, H., Yang, D., Barszczyk, A., Vempala, N., Wei, J., Wu, S.J., Zheng, P.P., Fu, G., Lee, K., Feng, Z.-P.: Smartphone-based blood pressure measurement using transdermal optical imaging technology. Circ.: Cardiovasc. Imaging 12(8), e008857 (2019)

    Google Scholar 

  69. Shen, W., Newsham, G., Gunay, B.: Leveraging existing occupancy-related data for optimal control of commercial office buildings: a review. Adv. Eng. Inform. 33, 230–242 (2017)

    CrossRef  Google Scholar 

  70. Gu, C.: Short-range noncontact sensors for healthcare and other emerging applications: a review. Sensors 16(8), 1169 (2016)

    CrossRef  Google Scholar 

  71. Kalyanaraman, A., Soltanaghaei, E., Whitehouse, K.: Doorpler: a radar-based system for real-time, low power zone occupancy sensing. In: 2019 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), pp. 42–53. IEEE (2019)

    Google Scholar 

  72. Gurbuz, S.Z., Amin, M.G.: Radar-based human-motion recognition with deep learning: promising applications for indoor monitoring. IEEE Signal Process. Mag. 36(4), 16–28 (2019)

    CrossRef  Google Scholar 

  73. Yavari, E., Jou, H., Lubecke, V., Boric-Lubecke, O.: Doppler radar sensor for occupancy monitoring. In: 2013 IEEE Topical Conference on Power Amplifiers for Wireless and Radio Applications, pp. 145–147. IEEE (2013)

    Google Scholar 

  74. Sadreazami, H., Bolic, M., Rajan, S.: TL-fall: contactless indoor fall detection using transfer learning from a pretrained model. In: 2019 IEEE International Symposium on Medical Measurements and Applications (MeMeA), pp. 1–5. IEEE (2019)

    Google Scholar 

  75. Sadreazami, H., Bolic, M., Rajan, S.: Fall detection using standoff radar-based sensing and deep convolutional neural network. IEEE Trans. Circuits Syst. II Express Briefs 67(1), 197–201 (2019)

    CrossRef  Google Scholar 

  76. Li, H., Shrestha, A., Heidari, H., Le Kernec, J., Fioranelli, F.: Bi-LSTM network for multimodal continuous human activity recognition and fall detection. IEEE Sens. J. 20(3), 1191–1201 (2019)

    CrossRef  Google Scholar 

  77. Girão, P.S., Postolache, O., Postolache, G., Ramos, P., Pereira, J.D.: Microwave doppler radar in unobtrusive health monitoring. In: Journal of Physics: Conference Series, vol. 588, no. 1, p. 012046. IOP Publishing (2015)

    Google Scholar 

  78. Pisa, S., Pittella, E., Piuzzi, E.: A survey of radar systems for medical applications. IEEE Aerosp. Electron. Syst. Mag. 31(11), 64–81 (2016)

    CrossRef  Google Scholar 

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Tabassum, A., Ahad, M.A.R. (2021). Biomedical Radar and Antenna Systems for Contactless Human Activity Analysis. In: Ahad, M.A.R., Inoue, A. (eds) Vision, Sensing and Analytics: Integrative Approaches. Intelligent Systems Reference Library, vol 207. Springer, Cham. https://doi.org/10.1007/978-3-030-75490-7_8

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