Abstract
Noncontact vital sign monitoring based on radar has attracted great interest in many fields. Heart rate variability(HRV), which measures the fluctuation of heartbeat intervals, has been considered an important indicator for general health evaluation. In this paper, we proposed a new algorithm for HRV monitoring using frequency-modulated-continuous-wave (FMCW) radar. We calculate the acceleration of the reflected signal to enhance the heartbeat and suppress the impact of respiration. Finally, a joint optimization algorithm is used to segment the acceleration signal and the time interval of each heartbeat can be extracted for analyzing HRV. Experimental results over 10 participants show the potential of the proposed algorithm for noncontact HRV estimation with high accuracy. The results indicate the possibility for the algorithm to be employed in emotion recognition, sleep, and heart disease monitoring.
Supported in part by the National Natural Science Foundation of China (NSFC) under Award 52175033 and Award U21A20120, in part by the Zhejiang Provincial Natural Science Foundation under Award LZ20E050002.
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References
Silveri, G., et al.: Identification of ischemic heart disease by using machine learning technique based on parameters measuring heart rate variability. In: 2020 28th European Signal Processing Conference (EUSIPCO), pp. 1309–1312. IEEE (2021)
Kirtana, R., Lokeswari, Y.: An IoT based remote HRV monitoring system for hypertensive patients. In: 2017 International Conference on Computer, Communication and Signal Processing (ICCCSP), pp. 1–6. IEEE (2017)
Gandhi, S., Baghini, M.S., Mukherji, S.: Mental stress assessment-a comparison between HRV based and respiration based techniques. In: 2015 Computing in Cardiology Conference (CinC), pp. 1029–1032. IEEE (2015)
Szypulska, M., Piotrowski, Z.: Prediction of fatigue and sleep onset using HRV analysis. In: Proceedings of the 19th International Conference Mixed Design of Integrated Circuits and Systems-MIXDES 2012, pp. 543–546. IEEE (2012)
Faust, O., et al.: Heart rate variability for medical decision support systems: a review. Comput. Biol. Med. 145, 105407 (2022)
Brüser, C., Antink, C.H., Wartzek, T., Walter, M., Leonhardt, S.: Ambient and unobtrusive cardiorespiratory monitoring techniques. IEEE Rev. Biomed. Eng. 8, 30–43 (2015)
Wang, P., et al.: Research progress in millimeter wave radar-based non-contact sleep monitoring-a review. In: 2021 13th International Symposium on Antennas, Propagation and EM Theory (ISAPE), pp. 1–3. IEEE (2021)
Hu, W., Zhao, Z., Wang, Y., Zhang, H., Lin, F.: Noncontact accurate measurement of cardiopulmonary activity using a compact quadrature doppler radar sensor. IEEE Trans. Biomed. Eng. 61(3), 725–735 (2013)
Al-Naji, A., Gibson, K., Lee, S.H., Chahl, J.: Monitoring of cardiorespiratory signal: principles of remote measurements and review of methods. IEEE Access 5, 15776–15790 (2017)
Wang, G., Gu, C., Inoue, T., Li, C.: A hybrid FMCW-interferometry radar for indoor precise positioning and versatile life activity monitoring. IEEE Trans. Microw. Theory Tech. 62(11), 2812–2822 (2014)
Zhai, Q., Han, X., Han, Y., Yi, J., Wang, S., Liu, T.: A contactless on-bed radar system for human respiration monitoring. IEEE Trans. Instrum. Meas. 71, 1–10 (2022)
Wiesner, A.: A multifrequency interferometric CW radar for vital signs detection. In: 2009 IEEE Radar Conference, pp. 1–4. IEEE (2009)
Rathna, G., Meshineni, D.: Analysis of FM CW-radar signals to extract vital-sign information. In: 2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), pp. 1–6. IEEE (2021)
Zhu, Z., Yang, D., Zhao, R., Liang, B.: Vital sign signal extraction method based on permutation entropy and EMD algorithm for ultra-wideband radar. In: 2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE), pp. 1268–1273. IEEE (2019)
Zhao, M., Adib, F., Katabi, D.: Emotion recognition using wireless signals. In: Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, pp. 95–108 (2016)
Xiong, Y., Peng, Z., Gu, C., Li, S., Wang, D., Zhang, W.: Differential enhancement method for robust and accurate heart rate monitoring via microwave vital sign sensing. IEEE Trans. Instrum. Meas. 69(9), 7108–7118 (2020)
Lv, W., Zhao, Y., Zhang, W., Liu, W., Hu, A., Miao, J.: Remote measurement of short-term heart rate with narrow beam millimeter wave radar. IEEE Access 9, 165049–165058 (2021)
Wang, F., Zeng, X., Wu, C., Wang, B., Liu, K.R.: Radio frequency based heart rate variability monitoring. In: ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8007–8011. IEEE (2021)
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Han, X., Liu, T. (2023). Noncontact Heart Rate Variability Monitoring Based on FMCW Radar. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14268. Springer, Singapore. https://doi.org/10.1007/978-981-99-6486-4_19
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DOI: https://doi.org/10.1007/978-981-99-6486-4_19
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