Department of Electronics, School of Biomedical Engineering
The Fourth Military Medical University
China
HomepageSchool of Biomedical Engineering
The Fourth Military Medical University
China
HomepageDepartment of Medical Electronics, School of Biomedical Engineering
The Fourth Military Medical University
China
Homepage1. Borek, S. E., B. J. Clarke, and P. J. Costianes, "Through-the-wall surveillance for homeland security and law enforcement," Proc SPIE, Vol. 5778, 175-185, 2005.
doi:10.1117/12.602897
2. Burchett, H., "Advances in through wall radar for search, rescue and security applications," 2006 IET Conference on Crime and Security, 511-525, London, UK, 2006.
3. Staderini, E. M., "UWB radars in medicine," IEEE Aeros. Elec. Sys. Mag., Vol. 17, No. 1, 13-18, 2002.
doi:10.1109/62.978359
4. Ernestina, C. and G. Bharat, "FM-UWB for communications and radar in medical applications," Wireless. Pers. Commun., Vol. 51, 793-809, 2009.
5. Chang, J., C. Paulson, and P. Welsh, "Development of micropower ultrawideband impulse radar medical diagnostic systems for continuous monitoring applications and austere environments," 2012 IEEE Radar Conference, 699-704, 2012.
doi:10.1109/RADAR.2012.6212228
6. Gu, C. Z. and C. Z. Li, "From tumor targeting to speech monitoring: Accurate respiratory monitoring using medical continuous-wave radar sensors," IEEE Microwave Magazine, Vol. 15, 66-76, 2014.
7. Mostov, K., E. Liptsen, and R. Boutchko, "Medical applications of shortwave FM radar: Remote monitoring of cardiac and respiratory motion," Medical Physics, Vol. 37, No. 3, 1332-1338, 2010.
doi:10.1118/1.3267038
8. Kim, Y., S. Ha, and J. Kwon, "Human detection using doppler radar based on physical characteristics of targets," IEEE Geoscience and Remote Sensing Letters, Vol. 12, No. 2, 289-293, 2015.
doi:10.1109/LGRS.2014.2336231
9. Nanzer, J. A., "A review of microwave wireless techniques for human presence detection and classification," IEEE Transactions on Microwave Theory and Techniques, Vol. 65, No. 5, 1780-1794, 2017.
doi:10.1109/TMTT.2017.2650909
10. Liang, F. L., F. G. Qi, Q. An, H. Lv, F. M. Chen, Z. Li, and J. Q. Wang, "Detection of multiple stationary humans using UWB MIMO radar," Sensors, Vol. 16, No. 11, 1922-1938, Basel, Switzerland, 2016.
doi:10.3390/s16111922
11. Li, J., Z. Zeng, J. Sun, and F. Liu, "Through-wall detection of human Being's movement by UWB radar," IEEE Geoscience and Remote Sensing Letters, Vol. 9, No. 6, 1079-1083, 2012.
doi:10.1109/LGRS.2012.2190707
12. Thiel, M. and K. Sarabandi, "Ultra wideband multi-static scattering analysis of human movement within buildings for the purpose of stand-off detection and localization," IEEE Trans. Antennas Propag., Vol. 59, 1261-1268, 2011.
doi:10.1109/TAP.2011.2109349
13. Van, N., A. Q. Javaid, and M. A. Weitnauer, "Detection of motion and posture change using an IR-UWB radar," 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 3650-3653, Orlando, FL, USA, 2016.
14. Kiasari, M. A., S. Y. Na, J. Y. Kim, and Y. Won, "Monitoring human behavior patterns using ultra-wide band radar based on neural networks," Asia Life Sciences, 13-29, 2015.
15. Zhai, S. J. and T. Jiang, "Target detection and classification by measuring and processing bistatic UWB radar signal," Measurement, Vol. 47, 547-557, 2014.
doi:10.1016/j.measurement.2013.08.031
16. Bryan, J. D., J. Kwon, N. Lee, and Y. Kim, "Application of ultra-wide band radar for classification of human activities," IET Radar, Sonar & Navigation, Vol. 6, No. 3, 172-179, 2012.
doi:10.1049/iet-rsn.2011.0101
17. Lv, H., G. H. Lu, X. J. Jing, and J. Q. Wang, "A new ultra-wideband radar for detecting survivors buried under earthquake rubbles," Microwave & Optical Technology Letters, Vol. 52, No. 11, 2621-2624, 2010.
doi:10.1002/mop.25539
18. Wang, J. Q., C. X. Zheng, G. H. Lu, and X. J. Jing, "A new method for identifying the life parameters via radar," EURASIP Journal on Advances in Signal Processing, Vol. 2007, No. 1, 1-8, 2007.
doi:10.1155/2007/89264
19. Zhang, Y., F. M. Chen, H. J. Xue, Z. Li, Q. An, J. Q. Wang, and Y. Zhang, "Detection and identification of multiple stationary human targets via bio-radar based on the cross-correlation method," Sensors, Vol. 16, No. 11, 1793-1804, 2016.
doi:10.3390/s16111793
20. Liang, F. L., F. G. Qi, Q. An, H. Lv, F. M. Chen, Z. Li, and J. Q. Wang, "Detection of multiple stationary humans using UWB MIMO radar," Sensors, Vol. 16, No. 11, 1922-1938, Basel, Switzerland, 2016.
doi:10.3390/s16111922
21. Lv, H., F. G. Qi, Y. Zhang, T. Jiao, F. L. Liang, Z. Li, and J. Q. Wang, "Improved detection of human respiration using data fusion based on a multistatic UWB radar," Remote Sensing, Vol. 8, No. 9, 773-791, 2016.
doi:10.3390/rs8090773
22. Lv, H., W. Li, Z. Li, Y. Zhang, T. Jiao, H. J. Xue, M. Liu, X. J. Jing, and J. Q. Wang, "Characterization and identification of IR-UWB respiratory-motion response of trapped victims," IEEE Trans. Geosci. Remote Sens., Vol. 52, 7195-7204, 2014.
doi:10.1109/TGRS.2014.2309141
23. Yu, X., T. J. Jiao, H. Lv, Y. Zhang, Z. Li, and J. Q. Wang, "A new use of UWB radar to detecting victims and discriminating humans from animals," 2016 16th International Conference on Ground Penetrating Radar (GPR), 1-5, Hong Kong, China, June 2016.
24. Wang, Y., X. Yu, Y. Zhang, H. Lv, T. Jiao, G. Lu, W. Z. Li, Z. Li, X. Jing, and J. Wang, "Using wavelet entropy to distinguish between humans and dogs detected by UWB radar," Progress In Electromagnetics Research, Vol. 139, 335-352, 2013.
doi:10.2528/PIER13032508
25. Yin, Y., X. Yu, H. Lv, F. G. Qi, Z. Q. Zhang, and J. Q. Wang, "Micro-vibration distinguishment of radar between humans and animals based on EEMD and energy ratio characteristics," China Medical Devices, Vol. 33, No. 10, 27-31, 2018.
26. Nunez, T. C., "Cotton BA transfusion therapy in hemorrhagic shock," Curr. Opin. Crit. Care, Vol. 15, 536-541, 2009.
doi:10.1097/MCC.0b013e328331575b
27. Matsui, T., T. Ishizuka, B. Takase, M. Ishihara, and M. Kikuchi, "Non-contact determination of vital sign alterations in hypovolaemic states induced by massive haemorrhage: An experimental attempt to monitor the condition of injured persons behind barriers or under disaster rubble," Medical and Biological Engineering and Computing, Vol. 42, No. 6, 807-811, 2004.
doi:10.1007/BF02345214
28. Wang, D. W., Y. Li, and R. Y. Peng, "Characters of the kinds and severity of injuries in deeply buried wounded personnel due to disaster and the monitoring of their vital sign," J. Trauma. Surg., Vol. 19, No. 10, 792-795, 2017.
29. Azriel, P., R. Pizov, and C. Shamay, "Systolic blood pressure variation is a sensitive indicator of hypovolemia in ventilated dogs subjected to graded hemorrhage," Anesthesiology, Vol. 67, 498-502, 1987.
30. Stern, A., C. D. Susan, B. P. Steven, and X. Wang, "Effect of blood pressure on haemorrhage volume and survival in a nearfatal haemorrhage model incorporating a vascular injury," Annals of Emergency Medicine, Vol. 22, 155-163, 1993.
doi:10.1016/S0196-0644(05)80195-7
31. Fulop, A., Z. Turoczi, D. Garbaisz, L. Harsanyi, and A. Szijarto, "Experimental models of hemorrhagic shock: A review," European Surgical Research, Vol. 50, No. 2, 57-70, 2013.
doi:10.1159/000348808
32. Gutierrez, G. and H. D. Reines, "Wulf-gutierrez ME clinical review: Hemorrhagic shock," Crit. Care, Vol. 8, 373-381, 2004.
doi:10.1186/cc2851
33. Shannon, C. E., "A mathematical theory of communication," ACM SIGMOBILE Mobile Computing and Communication Review, Vol. 5, No. 1, 3-55, 1948.
doi:10.1145/584091.584093
34. Hasan, A. A., S. P. Joseph, C. Z. Wendy, F. H. Daniel, and V. T. Nitish, "Wavelet entropy for subband segmentation of EEG during injury and recovery," Annals of Biomedical Engineering, Vol. 31, 653-658, 2003.
35. Cover, T. M. and P. E. Hart, "Nearest neighbor pattern classification," IEEE Transactions on Information Theory, Vol. 13, No. 1, 21-27, 1967.
doi:10.1109/TIT.1967.1053964
36. Hand, D., H. Mannila, and P. Smyth, Principles of Data Mining, The MIT Press, 2013.
37. Zhang, H., C. B. Alexander, M. Michael, and M. Jitendra, "SVM-KNN: Discriminative nearest neighbor classification for visual category recognition," 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2126-2136, New York, US, 2006.