Abstract
Remote sensing of vital signals without contact is important for many applications. Radars that perform this detection are called bio-radar. Bio-radar provides accurate measurement of vital signals using the Doppler principle with the change of chest wall movement caused by a person's breathing and heartbeat. In this study, non-contact vital signs (respiration, heart rate) measurements for human subject were performed using a low cost continuous wave (CW) Doppler radar with a 24 GHz operating frequency. Two different methods have been used to process the signals obtained from the measurements. While the first method is based on the Fast Fourier Transform (FFT), the second method uses the Multi-Resolution Analysis (MRA) method based on the Wavelet method. The results obtained by the first and second methods for respiration are 3.75% and 0% error rates, respectively. These values for heartbeat are 9.35% and 8.45%. These results show that radars can be used successfully for medical applications.
Keywords
Doppler radar Radar signal processing Vital signs detection Non-contact measurement Bio-radar
References
- Abdul-Atty, M.M., Amar, A.S.I. ve Mabrouk, M., 2020, “C-Band FMCW Radar Design and Implementation for Breathing Rate Estimation”, Advances in Science, Technology and Engineering Systems Journal, cilt. 5, no. 5, ss. 1299-1307.
- Acar, Y. E., Saritas, I. ve Yaldiz, E., 2021, “An Experimental Study: Detecting the Respiration Rates of Multiple Stationary Human Targets by Stepped Frequency Continuous Wave Radar”, Measurement, cilt.167,108268.
- Adib, F., Mao, H., Kabelac, Z., Katabi, D. ve Miller, R. C. “Smart homes that monitor breathing and heart rate”, Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, ss.837-846, 2015.
- Amin, M., 2017, Radar for indoor monitoring: detection, classification, and assessment, CRC Press.
- Andersen N., Granhaug, K., Michaelsen, J. A., Bagga, S., Hjortland, H. A., Knutsen, M. R., ve 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, cilt.52, no.12, ss.3421-3433.
- Anishchenko, L., Zhuravlev, A. ve Chizh, M., 2019, “Fall detection using multiple bioradars and convolutional neural networks”, Sensors, cilt.19 no.24, ss.5569.
- Azevedo, S. ve McEwan, T. E., 1997,“Micropower impulse radar”, IEEE Potentials, cilt.16 no.2, ss.15-20. Hu, W., Zhao, Z., Wang, Y., Zhang, H. ve Lin, F., 2013, “Noncontact accurate measurement of cardiopulmonary activity using a compact quadrature Doppler radar sensor”, IEEE Transactions on Biomedical Engineering, cilt.61 no.3, ss.725-735.
- Islam, Shekh MM, Motoyama, N., Pacheco, S. ve Lubecke, V. M.. “Non-Contact Vital Signs Monitoring for Multiple Subjects Using a Millimeter Wave FMCW Automotive Radar ”, IEEE/MTT-S International Microwave Symposium (IMS),ss.783-786, 2020.
- K-LC6 Radar Modülü. https://www.rfbeam.ch/product?id=12, ziyaret tarihi: 14.08.2020.
- Lin, F., Zhuang, Y., Song, C., Wang, A., Li, Y., Gu, C. ve Xu, W., 2016, “SleepSense: A noncontact and cost-effective sleep monitoring system”, IEEE Transactions on Biomedical Circuits and Systems, cilt.11 no.1, ss.189-202.
- Mallat, SG., 1989, “A theory for multiresolution signal decomposition: the wavelet representation”, IEEE Trans Pattern Anal Mach Intell, cilt.11 no.7 s.674–693.
- Qi, F., Li, C., Wang, S., Zhang, H., Wang, J. ve Lu, G., 2016, “Contact-free detection of obstructive sleep apnea based on wavelet information entropy spectrum using bio-radar”, Entropy, cilt.18 no.8, ss.306.
- Seflek, I., Acar, Y. E. ve Yaldiz, E., 2020, “Small Motion Detection and Non-Contact Vital Signs Monitoring with Continuous Wave Doppler Radars”, Elektronika ir Elektrotechnika, cilt.26 no.3, ss.54-60.
Abstract
Hayati sinyallerin temassız olarak uzaktan algılanması birçok uygulama açısından önem arz etmektedir. Bu algılamayı gerçekleştiren radarlar biyoradar olarak adlandırılmaktadır. Biyoradar kişinin solunum ve kalp atışından kaynaklanan göğüs duvarı hareketinin değişimiyle Doppler prensibini kullanarak hayati sinyallerin doğru bir şekilde ölçülmesini sağlamaktadır. Bu çalışmada, 24 GHz çalışma frekansına sahip düşük maliyetli sürekli dalga (CW) Doppler radarı kullanılarak insan denekten temassız bir şekilde yaşamsal belirti (solunum, kalp atış hızı) ölçümleri gerçekleştirilmiştir. Ölçümlerden elde edilen sinyallerin işlenmesinde iki farklı yöntem kullanılmıştır. İlk yöntem Hızlı Fourier Dönüşümünü (FFT) esas alırken ikinci yöntemde Dalgacık yöntemine dayalı Çoklu Çözünürlük Analizi (MRA) yöntemi kullanılmaktadır. Solunum hızında birinci ve ikinci yöntem için elde edilen sonuçlar %3.75 ve %0’ hata oranlıdır. Kalp atışı için sırasıyla %9.35 ve %8.45 hata oranlı değerler elde edilmiştir. Bu sonuçlar özellikle radarların tıbbi uygulamalar için başarıyla kullanılabileceğini göstermektedir.
References
- Abdul-Atty, M.M., Amar, A.S.I. ve Mabrouk, M., 2020, “C-Band FMCW Radar Design and Implementation for Breathing Rate Estimation”, Advances in Science, Technology and Engineering Systems Journal, cilt. 5, no. 5, ss. 1299-1307.
- Acar, Y. E., Saritas, I. ve Yaldiz, E., 2021, “An Experimental Study: Detecting the Respiration Rates of Multiple Stationary Human Targets by Stepped Frequency Continuous Wave Radar”, Measurement, cilt.167,108268.
- Adib, F., Mao, H., Kabelac, Z., Katabi, D. ve Miller, R. C. “Smart homes that monitor breathing and heart rate”, Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, ss.837-846, 2015.
- Amin, M., 2017, Radar for indoor monitoring: detection, classification, and assessment, CRC Press.
- Andersen N., Granhaug, K., Michaelsen, J. A., Bagga, S., Hjortland, H. A., Knutsen, M. R., ve 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, cilt.52, no.12, ss.3421-3433.
- Anishchenko, L., Zhuravlev, A. ve Chizh, M., 2019, “Fall detection using multiple bioradars and convolutional neural networks”, Sensors, cilt.19 no.24, ss.5569.
- Azevedo, S. ve McEwan, T. E., 1997,“Micropower impulse radar”, IEEE Potentials, cilt.16 no.2, ss.15-20. Hu, W., Zhao, Z., Wang, Y., Zhang, H. ve Lin, F., 2013, “Noncontact accurate measurement of cardiopulmonary activity using a compact quadrature Doppler radar sensor”, IEEE Transactions on Biomedical Engineering, cilt.61 no.3, ss.725-735.
- Islam, Shekh MM, Motoyama, N., Pacheco, S. ve Lubecke, V. M.. “Non-Contact Vital Signs Monitoring for Multiple Subjects Using a Millimeter Wave FMCW Automotive Radar ”, IEEE/MTT-S International Microwave Symposium (IMS),ss.783-786, 2020.
- K-LC6 Radar Modülü. https://www.rfbeam.ch/product?id=12, ziyaret tarihi: 14.08.2020.
- Lin, F., Zhuang, Y., Song, C., Wang, A., Li, Y., Gu, C. ve Xu, W., 2016, “SleepSense: A noncontact and cost-effective sleep monitoring system”, IEEE Transactions on Biomedical Circuits and Systems, cilt.11 no.1, ss.189-202.
- Mallat, SG., 1989, “A theory for multiresolution signal decomposition: the wavelet representation”, IEEE Trans Pattern Anal Mach Intell, cilt.11 no.7 s.674–693.
- Qi, F., Li, C., Wang, S., Zhang, H., Wang, J. ve Lu, G., 2016, “Contact-free detection of obstructive sleep apnea based on wavelet information entropy spectrum using bio-radar”, Entropy, cilt.18 no.8, ss.306.
- Seflek, I., Acar, Y. E. ve Yaldiz, E., 2020, “Small Motion Detection and Non-Contact Vital Signs Monitoring with Continuous Wave Doppler Radars”, Elektronika ir Elektrotechnika, cilt.26 no.3, ss.54-60.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Article |
| Authors | |
| Publication Date | December 31, 2020 |
| Submission Date | November 5, 2020 |
| Acceptance Date | December 1, 2020 |
| Published in Issue | Year 2020 |