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Non-Contact Detection of Simulated Vital Signs with Frequency Modulated Continuous Wave Radar

Year 2020, Ejosat Special Issue 2020 (ICCEES), 72 - 77, 05.10.2020
https://doi.org/10.31590/ejosat.802905

Abstract

The recent use of radars in indoor applications has made them a part of live. The probability of seeing radars anywhere in living area (house, car, street) has increased considerably. In parallel with this increase, radar applications that make life easier have emerged. In particular, the ability of radars to detect the presence of an object without contact has enabled them to find their place in medical applications. Non-contact detection of vital signs with radars is among the remarkable studies recently. Since there is no contact situation (probe, etc.) for the patient in this determination, it provides freedom of movement and also facilitates the work for those who will perform the surveillance. The simple structure of the Frequency Modulated Continuous Wave Radar (FMCW), its low cost, its ability to detect range and its less susceptibility to noise compared to pulse radars make it one step ahead of other radars. In addition, the disadvantage of continuous wave radars (CW) that cannot detect more than one target is eliminated by FMCW radar. FMCW can distinguish multiple targets from each other, depending on the radar range resolution. In this study, chest wall motion due to respiration and heartbeat was simulated and detected by FMCW radar. An algorithm has been presented to make the detection. First of all, the range of the targets is determined and then the vital signs are calculated. By using multiple stationary targets, targets at 5 and 8 meters are detected with 0% and 1.56% error rates, respectively. Respiration and heart rates present at these targets are determined with an error rate of 2.29% for both targets, respectively. The preliminary results show that the FMCW radar has high success in detecting range and the existence of vital signs originating from displacement. It is anticipated that in the future, applications carried out with contact measurements will be replaced by radars.

References

  • Muñoz-Ferreras, J. M., Wang, J., Peng, Z., Li, C., & Gómez-García, R. (2019, May). Fmcw-radar-based vital-sign monitoring of multiple patients. In 2019 IEEE MTT-S International Microwave Biomedical Conference (IMBioC) (Vol. 1, pp. 1-3). IEEE.
  • Andersen, N., Granhaug, K., Michaelsen, J. A., Bagga, S., Hjortland, H. A., Knutsen, M. R., ... & Wisland, D. T. (2017). A 118-mw pulse-based radar soc in 55-nm cmos for non-contact human vital signs detection. IEEE Journal of Solid-State Circuits, 52(12), 3421-3433.
  • Alizadeh, M., Shaker, G., De Almeida, J. C. M., Morita, P. P., & Safavi-Naeini, S. (2019). Remote monitoring of human vital signs using mm-Wave FMCW radar. IEEE Access, 7, 54958-54968.
  • Anishchenko, L., Zhuravlev, A., & Chizh, M. (2019). Fall Detection Using Multiple Bioradars and Convolutional Neural Networks. Sensors, 19(24), 5569.
  • Kagawa, M., Suzumura, K., & Matsui, T. (2016, August). Sleep stage classification by non-contact vital signs indices using Doppler radar sensors. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 4913-4916). IEEE.
  • Li, C., Cummings, J., Lam, J., Graves, E., & Wu, W. (2009). Radar remote monitoring of vital signs. IEEE Microwave Magazine, 10(1), 47-56.
  • Tran, V. P., Al-Jumaily, A. A., & Islam, S. M. S. (2019). Doppler radar-based non-contact health monitoring for obstructive sleep apnea diagnosis: A comprehensive review. Big Data and Cognitive Computing, 3(1), 3.
  • Lin, F., Zhuang, Y., Song, C., Wang, A., Li, Y., Gu, C., ... & Xu, W. (2016). SleepSense: A noncontact and cost-effective sleep monitoring system. IEEE transactions on biomedical circuits and systems, 11(1), 189-202.
  • Adib, F., Mao, H., Kabelac, Z., Katabi, D., & Miller, R. C. (2015, April). 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).
  • Hu, W., Zhao, Z., Wang, Y., Zhang, H., & Lin, F. (2013). Noncontact accurate measurement of cardiopulmonary activity using a compact quadrature Doppler radar sensor. IEEE Transactions on Biomedical Engineering, 61(3), 725-735.
  • Tu, J., Hwang, T., & Lin, J. (2016). Respiration rate measurement under 1-D body motion using single continuous-wave Doppler radar vital sign detection system. IEEE Transactions on Microwave Theory and Techniques, 64(6), 1937-1946.
  • Seflek, I., Acar, Y. E., & Yaldiz, E. (2020). Small Motion Detection and Non-Contact Vital Signs Monitoring with Continuous Wave Doppler Radars. Elektronika ir Elektrotechnika, 26(3), 54-60.
  • He, M., Nian, Y., & Gong, Y. (2017). Novel signal processing method for vital sign monitoring using FMCW radar. Biomedical Signal Processing and Control, 33, 335-345.
  • Lee, H., Kim, B. H., Park, J. K., Kim, S. W., & Yook, J. G. (2019). A resolution enhancement technique for remote monitoring of the vital signs of multiple subjects using a 24 GHz bandwidth-limited FMCW radar. IEEE Access, 8, 1240-1248.
  • Ahmad, A., Roh, J. C., Wang, D., & Dubey, A. (2018, April). Vital signs monitoring of multiple people using a FMCW millimeter-wave sensor. In 2018 IEEE Radar Conference (RadarConf18) (pp. 1450-1455). IEEE.
  • Mercuri, M., Lorato, I. R., Liu, Y. H., Wieringa, F., Van Hoof, C., & Torfs, T. (2019). Vital-sign monitoring and spatial tracking of multiple people using a contactless radar-based sensor. Nature Electronics, 2(6), 252-262.

Frekans Modüleli Sürekli Dalga Radarıyla Simüle Edilen Hayati Sinyallerin Temassız Tespiti

Year 2020, Ejosat Special Issue 2020 (ICCEES), 72 - 77, 05.10.2020
https://doi.org/10.31590/ejosat.802905

Abstract

Radarların son dönemde iç ortam uygulamalarında da kullanılabilmeleri onları hayatın bir parçası haline getirmiştir. Yaşam alanının herhangi bir yerinde (ev, araç, sokak) radarlara rastlama olasılığı oldukça artmıştır. Bu artışa paralel olarak hayatı kolaylaştıran radar uygulamaları da ortaya çıkmıştır. Özellikle radarların bir nesnenin varlığını temassız tespit edebilme yeteneği onların tıp uygulamalarında da yerini bulmasını sağlamıştır. Hayati belirtilerin radarlarla temassız tespiti son dönemlerde dikkat çeken çalışmalar arasında yerini almaktadır. Bu tespitte hasta için temaslı herhangi bir durum (prob vb.) söz konusu olmadığı için hareket serbestliği sağlamakta ayrıca gözetimi gerçekleştirecekler için işin kolaylaşmasına sebep olmaktadır. Frekans Modüleli Sürekli Dalga Radarının (FMCW) basit yapısı, ucuz maliyeti, menzil tespit edebilme yeteneği ve darbe radarlarına kıyasla gürültüden daha az etkilenmesi onu diğer radarlardan bir adım öne çıkarmaktadır. Ayrıca sürekli dalga radarlarının (CW) birden çok hedefi tespit edememe dezavantajı FMCW radar ile ortadan kaldırılmaktadır. FMCW radar menzil çözünürlüğüne bağlı olarak birden çok hedefi birbirinden ayırt edebilmektedir. Bu çalışmada, solunum ve kalp atışından kaynaklanan göğüs duvar hareketi simüle edilerek FMCW radarı tarafından tespiti gerçekleştirilmiştir. Tespitin gerçekleştirilebilmesi için bir algoritma sunulmuştur. Öncelikli olarak hedeflerin menzili tespit edilmiş daha sonra hayati sinyaller hesaplanmıştır. Çoklu sabit hedefler kullanılarak 5 ve 8 metre de bulunan hedefler sırasıyla %0 ve %1.56 hata oranları ile tespit edilmiştir. Bu hedeflerde mevcut olan solunum ve kalp atış hızları her iki hedef için sırasıyla %2.29 hata oranı ile hesaplanmıştır. Elde edilen ön sonuçlar FMCW radarın menzil ve yer değiştirme kaynaklı hayati sinyal varlığının tespitinde yüksek başarıya sahip olduğunu göstermektedir. Gelecekte temaslı ölçümlerle gerçekleştirilen uygulamaların yerini radarların alabileceği öngörülmektedir.

References

  • Muñoz-Ferreras, J. M., Wang, J., Peng, Z., Li, C., & Gómez-García, R. (2019, May). Fmcw-radar-based vital-sign monitoring of multiple patients. In 2019 IEEE MTT-S International Microwave Biomedical Conference (IMBioC) (Vol. 1, pp. 1-3). IEEE.
  • Andersen, N., Granhaug, K., Michaelsen, J. A., Bagga, S., Hjortland, H. A., Knutsen, M. R., ... & Wisland, D. T. (2017). A 118-mw pulse-based radar soc in 55-nm cmos for non-contact human vital signs detection. IEEE Journal of Solid-State Circuits, 52(12), 3421-3433.
  • Alizadeh, M., Shaker, G., De Almeida, J. C. M., Morita, P. P., & Safavi-Naeini, S. (2019). Remote monitoring of human vital signs using mm-Wave FMCW radar. IEEE Access, 7, 54958-54968.
  • Anishchenko, L., Zhuravlev, A., & Chizh, M. (2019). Fall Detection Using Multiple Bioradars and Convolutional Neural Networks. Sensors, 19(24), 5569.
  • Kagawa, M., Suzumura, K., & Matsui, T. (2016, August). Sleep stage classification by non-contact vital signs indices using Doppler radar sensors. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 4913-4916). IEEE.
  • Li, C., Cummings, J., Lam, J., Graves, E., & Wu, W. (2009). Radar remote monitoring of vital signs. IEEE Microwave Magazine, 10(1), 47-56.
  • Tran, V. P., Al-Jumaily, A. A., & Islam, S. M. S. (2019). Doppler radar-based non-contact health monitoring for obstructive sleep apnea diagnosis: A comprehensive review. Big Data and Cognitive Computing, 3(1), 3.
  • Lin, F., Zhuang, Y., Song, C., Wang, A., Li, Y., Gu, C., ... & Xu, W. (2016). SleepSense: A noncontact and cost-effective sleep monitoring system. IEEE transactions on biomedical circuits and systems, 11(1), 189-202.
  • Adib, F., Mao, H., Kabelac, Z., Katabi, D., & Miller, R. C. (2015, April). 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).
  • Hu, W., Zhao, Z., Wang, Y., Zhang, H., & Lin, F. (2013). Noncontact accurate measurement of cardiopulmonary activity using a compact quadrature Doppler radar sensor. IEEE Transactions on Biomedical Engineering, 61(3), 725-735.
  • Tu, J., Hwang, T., & Lin, J. (2016). Respiration rate measurement under 1-D body motion using single continuous-wave Doppler radar vital sign detection system. IEEE Transactions on Microwave Theory and Techniques, 64(6), 1937-1946.
  • Seflek, I., Acar, Y. E., & Yaldiz, E. (2020). Small Motion Detection and Non-Contact Vital Signs Monitoring with Continuous Wave Doppler Radars. Elektronika ir Elektrotechnika, 26(3), 54-60.
  • He, M., Nian, Y., & Gong, Y. (2017). Novel signal processing method for vital sign monitoring using FMCW radar. Biomedical Signal Processing and Control, 33, 335-345.
  • Lee, H., Kim, B. H., Park, J. K., Kim, S. W., & Yook, J. G. (2019). A resolution enhancement technique for remote monitoring of the vital signs of multiple subjects using a 24 GHz bandwidth-limited FMCW radar. IEEE Access, 8, 1240-1248.
  • Ahmad, A., Roh, J. C., Wang, D., & Dubey, A. (2018, April). Vital signs monitoring of multiple people using a FMCW millimeter-wave sensor. In 2018 IEEE Radar Conference (RadarConf18) (pp. 1450-1455). IEEE.
  • Mercuri, M., Lorato, I. R., Liu, Y. H., Wieringa, F., Van Hoof, C., & Torfs, T. (2019). Vital-sign monitoring and spatial tracking of multiple people using a contactless radar-based sensor. Nature Electronics, 2(6), 252-262.
There are 16 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

İbrahim Şeflek 0000-0002-6782-9513

Ercan Yaldız 0000-0003-2245-0654

Publication Date October 5, 2020
Published in Issue Year 2020 Ejosat Special Issue 2020 (ICCEES)

Cite

APA Şeflek, İ., & Yaldız, E. (2020). Frekans Modüleli Sürekli Dalga Radarıyla Simüle Edilen Hayati Sinyallerin Temassız Tespiti. Avrupa Bilim Ve Teknoloji Dergisi72-77. https://doi.org/10.31590/ejosat.802905