Abstract
Recently, vital sign and sleep monitoring using wireless signals has made great progress. However, overnight respiration monitoring remains a challenge due to human unconscious and uncontrollable movements during sleep. In the paper, we explore the potential of an IR-UWB radar and implement a fine-grained overnight respiration monitoring prototype. Particularly, we exploit the complementarity between amplitude and phase of the radar signal to eliminate blind spots, thus improving the detection rate of overnight respiration monitoring. Moreover, we propose a circle fitting based phase restoration algorithm to correct the respiration depth distortion, and further recognize four respiration patterns (i.e., apnea pattern, Tachypnea pattern, Kussmaul pattern and rapid change pattern of respiration rate), thus enabling fine-grained respiration monitoring during overnight sleep. The experimental results show that our prototype achieves high respiration detection rates and accurate respiration rates, outperforming the two existing approaches. In addition, our prototype has captured the apnea pattern many times in the real sleep scenarios.
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Notes
- 1.
The data collection procedure was approved by the Institutional Review Board (IRB). Each volunteer is required to sign an informed consent form before the experiments.
References
Flow chest straps (2018). https://www.wareable.com/wearable-tech/sweetzpot-flow-breathing-chest-strap-2018
Abdelnasser, H., Harras, K.A., Youssef, M.: UbiBreathe: a ubiquitous non-invasive WiFi-based breathing estimator. In: Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 277–286 (2015)
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)
Anderson, J.A., Vann, W.F.: Respiratory monitoring during pediatric sedation: pulse oximetry and capnography. Pediatr. Dent. 10(2), 94–101 (1988)
Azagra-Calero, E., Espinar-Escalona, E., Barrera-Mora, J.M., Llamas-Carreras, J.M., Solano-Reina, E.: Obstructive sleep apnea syndrome (OSAS). Review of the literature. Medicina Oral, Patologia Oral y Cirugia Bucal 17(6), e925 (2012)
Chernov, N., Lesort, C.: Least squares fitting of circles. J. Math. Imaging Vis. 23(3), 239–252 (2005)
Jiang, C., Guo, J., He, Y., Jin, M., Li, S., Liu, Y.: mmVib: micrometer-level vibration measurement with mmwave radar. In: Proceedings of the 26th Annual International Conference on Mobile Computing and Networking, pp. 1–13 (2020)
Khamis, A., Kusy, B., Chou, C.T., Hu, W.: WiRelax: towards real-time respiratory biofeedback during meditation using WiFi. Ad Hoc Netw. 107, 102226 (2020)
Liu, J., Chen, Y., Wang, Y., Chen, X., Cheng, J., Yang, J.: Monitoring vital signs and postures during sleep using WiFi signals. IEEE Internet Things J. 5(3), 2071–2084 (2018)
Luo, J., Ying, K., Bai, J.: Savitzky-Golay smoothing and differentiation filter for even number data. Signal Process. 85(7), 1429–1434 (2005)
Młyńczak, M., Cybulski, G.: Improvement of body posture changes detection during ambulatory respiratory measurements using impedance pneumography signals. In: Kyriacou, E., Christofides, S., Pattichis, C.S. (eds.) XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016. IP, vol. 57, pp. 167–171. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-32703-7_34
Nandakumar, R., Gollakota, S., Watson, N.: Contactless sleep apnea detection on smartphones. In: Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services, pp. 45–57 (2015)
Raheel, M.S., et al.: Breathing and heartrate monitoring system using IR-UWB radar. In: 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), pp. 1–5. IEEE (2019)
Rahman, T., et al.: DoppleSleep: a contactless unobtrusive sleep sensing system using short-range doppler radar. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 39–50 (2015)
Vorona, R.D., Winn, M.P., Babineau, T.W., Eng, B.P., Feldman, H.R., Ware, J.C.: Overweight and obese patients in a primary care population report less sleep than patients with a normal body mass index. Arch. Intern. Med. 165(1), 25–30 (2005)
Wang, A., Sunshine, J.E., Gollakota, S.: Contactless infant monitoring using white noise. In: The 25th Annual International Conference on Mobile Computing and Networking, pp. 1–16 (2019)
Wang, H., et al.: Human respiration detection with commodity WiFi devices: do user location and body orientation matter? In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 25–36 (2016)
Wang, T., Zhang, D., Zheng, Y., Gu, T., Zhou, X., Dorizzi, B.: C-FMCW based contactless respiration detection using acoustic signal. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 1, no. 4, pp. 1–20 (2018)
Wang, Y., Zheng, Y.: TagBreathe: monitor breathing with commodity RFID systems. IEEE Trans. Mob. Comput. 19(4), 969–981 (2019)
Yang, Z., Pathak, P.H., Zeng, Y., Liran, X., Mohapatra, P.: Monitoring vital signs using millimeter wave. In: Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 211–220 (2016)
Yim, D.H., Cho, S.H.: An equidistance multi-human detection algorithm based on noise level using mono-static IR-UWB radar system. In: Future Communication, Information and Computer Science: Proceedings of the 2014 International Conference on Future Communication, Information and Computer Science (FCICS 2014), Beijing, China, 22–23 May 2014, p. 131. CRC Press (2015)
Zeng, Y., Wu, D., Gao, R., Gu, T., Zhang, D.: FullBreathe: full human respiration detection exploiting complementarity of CSI phase and amplitude of WiFi signals. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 2, no. 3, pp. 1–19 (2018)
Zeng, Y., Wu, D., Xiong, J., Yi, E., Gao, R., Zhang, D.: FarSense: pushing the range limit of WiFi-based respiration sensing with CSI ratio of two antennas. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, no. 3, pp. 1–26 (2019)
Zheng, T., Chen, Z., Cai, C., Luo, J., Zhang, X.: V2iFi: in-vehicle vital sign monitoring via compact RF sensing. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 4, no. 2, pp. 1–27 (2020)
Acknowledgments
This work was supported by the National Natural Science Foundation of China under Grants No. 61802373 and No. 62072450.
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Li, S., Wang, Z., Zhang, F., Jin, B. (2022). Fine-Grained Respiration Monitoring During Overnight Sleep Using IR-UWB Radar. In: Hara, T., Yamaguchi, H. (eds) Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-030-94822-1_5
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