Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review
Abstract
:1. Introduction
2. Non-Contact Doppler Radar Architecture
2.1. Heterodyne versus Homodyne Topology
2.2. Continuous-Wave versus Pulsed-Wave Architecture
2.3. Single versus Quadrature Architecture
3. Non-Contact Doppler Radar Principle
4. Sources of Noise in Non-Contact Doppler Radar
4.1. Clutter and DC Offset
4.2. Phase-Nulling or Null-Point
4.3. Others Sources of Noise
5. Non-Contact Doppler Radar Signal Processing
5.1. Clutter and DC Offset Cancellation
5.2. Phase-Nulling Cancellation
5.3. Multi-Targets and Motions Artefacts Cancellation
6. Categories of Non-Contact Doppler Radar Signal Processing Techniques
- Time-Frequency Analysis: this methodology uses time-series and frequency domain as the basis of signals analysis.
- Numerical Analysis: this methodology uses numerical techniques such as statistical, transformation and complex frequency as the basis of signals analysis.
- Classification & Training: this methodology utilizes machine learning methodologies and algorithms as the basis of signals analysis and predictions.
- Other Methodologies: these methodologies utilize experimental and mathematical modeling as the basis of signals analysis and estimations.
6.1. Time-Frequency Analysis
6.2. Numerical Analysis
6.3. Classification and Training
6.4. Other Methodologies
7. Ultra-Wide Band Doppler Radar
8. Challenges and Future Research Directions
- First, it is recommended that future research be broadened to include non-contact assessment of heart rate and heart rate variability, as well as, targeting sleep monitoring with “non-stationary” and “non-direct facing” subject measurements. Additionally, pulse pressure, intrapulmonary pressure, tidal volume, minute ventilation, air flow, oxygen saturation, and Cheyne-Stokes respirations estimations are also encouraged to be explored extensively. The future achievements in these areas will significantly contribute to the screening, diagnosing and monitoring of cardiovascular comorbidity in obstructive sleep apnea (OSA) patients. This will also lead to new opportunities and market potentials towards Cardiology in Sleep Disordered Breathing (SDB).
- Second, it is recommended that future research be broadened to include the complexity of sleep environment, such as noises associated with unpredictable body movements, body orientations, changes in sleeping posture, multi-subjects cancellation, undesired harmonics, and intermodulation. The future achievements in these areas will significantly contribute to the practical realization and commercialization of non-contact sleep monitoring and diagnosing technology.
9. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Young, T.; Palta, M.; Dempsey, J.; Skatrud, J.; Webber, S.; Badr, S. The Occurrence of Sleep-Disordered Breathing Among Middle-Aged Adults. N. Engl. J. Med. 1993, 328, 1230–1235. [Google Scholar] [CrossRef] [PubMed]
- Peppard, P.E.; Young, T.; Barnet, J.H.; Palta, M.; Hagen, E.W.; Hla, K.M. Increased Prevalence of Sleep-Disordered Breathing in Adults. Am. J. Epidemiol. 2013, 177, 1006–1014. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- American Academy of Sleep Medicine. International Classification of Sleep Disorders, Revised: Diagnostic and Coding Manual; American Academy of Sleep Medicine: Chicago, IL, USA, 2001. [Google Scholar]
- Leung, R.S.T.; Bradley, T.D. Sleep Apnea and Cardiovascular Disease. Am. J. Respir. Crit. Care Med. 2001, 164, 2147–2165. [Google Scholar] [CrossRef] [PubMed]
- Pedrosa, R.P.; Drager, L.F.; Gonzaga, C.C.; Sousa, M.G.; De Paula, L.K.G.; Amaro, A.C.S.; Amodeo, C.; Bortolotto, L.A.; Krieger, E.M.; Bradley, T.D.; et al. Obstructive Sleep Apnea: The Most Common Secondary Cause of Hypertension Associated With Resistant Hypertension. Hypertension 2011, 58, 811–817. [Google Scholar] [CrossRef] [PubMed]
- Aronsohn, R.S.; Whitmore, H.; Cauter, E.V.; Tasali, E. Impact of Untreated Obstructive Sleep Apnea on Glucose Control in Type 2 Diabetes. Am. J. Respir. Crit. Care Med. 2010, 181, 507–513. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Seicean, S.; Strohl, K.P.; Seicean, A.; Gibby, C.; Marwick, T.H. Sleep Disordered Breathing as a Risk of Cardiac Events in Subjects With Diabetes Mellitus and Normal Exercise Echocardiographic Findings. Am. J. Cardiol. 2013, 111, 1214–1220. [Google Scholar] [CrossRef] [PubMed]
- Nieto, F.J.; Peppard, P.E.; Young, T.; Finn, L.; Hla, K.M.; Farré, R. Sleep-disordered Breathing and Cancer Mortality: Results from the Wisconsin Sleep Cohort Study. Am. J. Respir. Crit. Care Med. 2012, 186, 190–194. [Google Scholar] [CrossRef] [PubMed]
- Young, T.; Skatrud, J.; Peppard, P.E. Risk Factors for Obstructive Sleep Apnea in Adults. J. Am. Med. Assoc. 2004, 291, 2013–2016. [Google Scholar] [CrossRef]
- Suzuki, Y.J.; Jain, V.; Park, A.-M.; Day, R.M. Oxidative stress and oxidant signaling in obstructive sleep apnea and associated cardiovascular diseases. Free Radic. Biol. Med. 2006, 40, 1683–1692. [Google Scholar] [CrossRef] [Green Version]
- Attarian, H.P.; Sabri, A.N. When to suspect obstructive sleep apnea syndrome. Symptoms may be subtle, but treatment is straightforward. Postgrad. Med. 2002, 111, 70–76. [Google Scholar] [CrossRef]
- Chazal, P.D.; O’Hare, E.; Fox, N.; Heneghan, C. Assessment of Sleep/Wake Patterns Using a Non-Contact Biomotion Sensor. In Proceedings of the 30th Annual International IEEE EMBS Conference, Vancouver, BC, Canada, 20–24 August 2008; pp. 514–517. [Google Scholar]
- Lie, D.Y.C.; Ichapurapu, R.; Jain, S.; Lopez, J.; Banister, R.E.; Nguyen, T.; Griswold, J. A 2.4 GHz Non-Contact Biosensor System for Continuous Monitoring of Vital-Signs. In Telemedicine Techniques and Applications; Graschew, G., Ed.; InTech: Rijeka, Croatia, 2011; pp. 211–238. [Google Scholar]
- Kagawa, M.; Ueki, K.; Tojima, H.; Matsui, T. Noncontact Screening System with Two Microwave Radars for the Diagnosis of Sleep Apnea-Hypopnea Syndrome. In Proceedings of the 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 3–7 July 2013; pp. 2052–2055. [Google Scholar]
- Kagawa, M.; Yoshida, Y.; Kubota, M.; Kurita, A.; Matsui, T. An overnight vital signs monitoring system for elderly people using dual microwave radars. In Proceedings of the Asia-Pacific Microwave Conference 2011, Melbourne, Australia, 5–8 December 2011; pp. 590–593. [Google Scholar]
- Ren, L.; Kong, L.; Foroughian, F.; Wang, H.; Theilmann, P.; Fathy, A.E. Comparison Study of Noncontact Vital Signs Detection Using a Doppler Stepped-Frequency Continuous-Wave Radar and Camera-Based Imaging Photoplethysmography. IEEE Trans. Microw. Theory Tech. 2017, 65, 3519–3529. [Google Scholar] [CrossRef]
- Savage, H.O.; Khushaba, R.N.; Zaffaroni, A.; Colefax, M.; Farrugia, S.; Schindhelm, K.; Teschler, H.; Weinreich, G.; Grueger, H.; Neddermann, M.; et al. Development and validation of a novel non-contact monitor of nocturnal respiration for identifying sleep-disordered breathing in patients with heart failure. ESC Heart Fail. 2016, 212–219. [Google Scholar] [CrossRef] [PubMed]
- Wang, H.; Cheng, J.-H.; Kao, J.-C.; Huang, T.-W. Review on Microwave/Millimeter-wave Systems for Vital Sign Detection. In Proceedings of the 2014 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet), Newport Beach, CA, USA, 19–23 January 2014; pp. 19–21. [Google Scholar]
- Hall, T.; Lie, D.Y.C.; Nguyen, T.Q.; Mayeda, J.C.; Lie, P.E.; Lopez, J.; Banister, R.E. Non-Contact Sensor for Long-Term Continuous Vital Signs Monitoring: A Review on Intelligent Phased-Array Doppler Sensor Design. Sensors 2017, 17, 2632. [Google Scholar] [CrossRef] [PubMed]
- Lin, C.-T.; Prasad, M.; Chung, C.-H.; Puthal, D.; El-Sayed, H.; Sankar, S.; Wang, Y.-K.; Singh, J.; Sangaiah, A.K. IoT-Based Wireless Polysomnography Intelligent System for Sleep Monitoring. IEEE Access 2018, 6, 405–414. [Google Scholar] [CrossRef]
- Yacchirema, D.C.; Sarabia-Jacome, D.; Palau, C.E.; Esteve, M. A Smart System for Sleep Monitoring by Integrating IoT With Big Data Analytics. IEEE Access 2018, 6, 35988–36001. [Google Scholar] [CrossRef]
- Matar, G.; Lina, J.-M.; Carrier, J.; Kaddoum, G. Unobtrusive Sleep Monitoring Using Cardiac, Breathing and Movements Activities: An Exhaustive Review. IEEE Access 2018, 6, 45129–45152. [Google Scholar] [CrossRef]
- Sadek, I.; Seet, E.; Biswas, J.; Abdulrazak, B.; Mokhtari, M. Nonintrusive Vital Signs Monitoring for Sleep Apnea Patients: A Preliminary Study. IEEE Access 2018, 6, 2506–2514. [Google Scholar] [CrossRef]
- Li, C.; Lubecke, V.; Boric-Lubecke, O.; Lin, J. A Review on Recent Advances in Doppler Radar Sensors for Noncontact Healthcare Monitoring. IEEE Trans. Microw. Theory Tech. 2013, 61, 2046–2060. [Google Scholar] [CrossRef]
- Scalise, L. Non Contact Heart Monitoring. In Advances in Electrocardiograms—Methods and Analysis; Millis, R., Ed.; InTech: Rijeka, Croatia, 2012; pp. 81–106. [Google Scholar]
- Ichapurapu, R.; Jain, S.; Kakade, M.U.; Lie, D.Y.C.; Banister, R.E. A 2.4 GHz Non-Contact Biosensor System for Continuous Vital-Signs Monitoring on a Single PCB. In Proceedings of the IEEE 8th International Conference, Changsha, China, 20–23 October 2009; pp. 925–928. [Google Scholar]
- Boric-Lubecke, O.; Lubecke, V.; Mostafanezhad, I.; Park, B.-K.; Massagram, W.; Jokanovic, B. Doppler Radar Architectures and Signal Processing for Heart Rate Extraction. Mikrotalasna Rev. 2009, 15, 12–17. [Google Scholar]
- Avagyan, H.; Hakhoumian, A.; Hayrapetyan, H.; Pogosyan, N.; Zakaryan, T. Portable Non-Contact Microwave Doppler Radar for Respiration and Heartbeat Sensing. Am. J. Phys. 2012, 5, 8–14. [Google Scholar]
- Postolache, O.A.; Girão, P.S.; Postolache, G. Comparative analysis of two systems for unobtrusive heart signal acquisition and characterization. In Proceedings of the 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 3–7 July 2013; pp. 7021–7024. [Google Scholar]
- Wang, G.; Munoz-Ferreras, J.-M.; Gu, C.; Li, C.; Gomez-Garcia, R. Linear-Frequency-Modulated Continuous-Wave Radar for Vital-Sign Monitoring. In Proceedings of the Wireless Sensors and Sensor Networks (WiSNet), Newport Beach, CA, USA, 19–23 January 2014; pp. 37–39. [Google Scholar]
- Wang, Y.; Liu, Q.; Fathy, A.E. CW and Pulse–Doppler Radar Processing Based on FPGA for Human Sensing Applications. IEEE Trans. Geosci. Remote Sens. 2013, 51, 3097–3107. [Google Scholar] [CrossRef]
- Lee, Y.S.; Pathirana, P.N.; Caelli, T.; Li, S. Further Applications of Doppler Radar for Non-contact Respiratory Assessment. In Proceedings of the 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 3–7 July 2013; pp. 3833–3836. [Google Scholar]
- Girbau, D.; Lázaro, A.; Ramos, Á.; Villarino, R. Remote Sensing of Vital Signs Using a Doppler Radar and Diversity to Overcome Null Detection. IEEE Sens. J. 2012, 12, 512–518. [Google Scholar] [CrossRef]
- Mostov, K.; Liptsen, E.; Boutchko, R. Medical applications of shortwave FM radar: Remote monitoring of cardiac and respiratory motion. Med. Phys. 2010, 37, 1332–1338. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Shouldice, R.B.; Heneghan, C.; Petres, G.; Zaffaroni, A.; Boyle, P.; McNicholas, W.T.; Chazal, P.D. Real Time Breathing Rate Estimation from a Non Contact Biosensor. In Proceedings of the 32nd Annual International Conference of the IEEE EMBS, Buenos Aires, Argentina, 31 August –4 September 2010; pp. 630–633. [Google Scholar]
- Vasu, V.; Heneghan, C.; Sezer, S.; Arumugam, T. Contact-free Estimation of Respiration Rates during Sleep. In Proceedings of the 22nd IET Irish Signals and Systems Conference, Dublin, Ireland, 23–24 June 2011. [Google Scholar]
- Ballal, T.; Shouldice, R.B.; Heneghan, C.; Zhu, A. Breathing Rate Estimation from a Non-Contact Biosensor Using an Adaptive IIR Notch Filter. In Proceedings of the Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS 2012), Santa Clara, CA, USA, 15–18 January 2012; pp. 5–8. [Google Scholar]
- Singh, A.; Baboli, M.; Gao, X.; Yavari, E.; Padasdao, B.; Soll, B.; Boric-Lubecke, O.; Lubecke, V. Considerations for Integration of a Physiological Radar Monitoring System with Gold Standard Clinical Sleep Monitoring Systems. In Proceedings of the 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 3–7 July 2013; pp. 2120–2123. [Google Scholar]
- Tran, V.P.; Al-Jumaily, A.A. Non-Contact Dual Pulse Doppler System based Respiratory and Heart Rates Estimation for CHF Patients. In Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, Italy, 25–29 August 2015; pp. 4202–4205. [Google Scholar]
- Tran, V.P.; Al-Jumaily, A.A. Non-Contact Dual Pulse Doppler System Based Real-Time Relative Demodulation and Respiratory & Heart Rates Estimations for Chronic Heart Failure Patients. Procedia Comput. Sci. 2015, 76, 47–52. [Google Scholar]
- Obeid, D.; Zaharia, G.; Sadek, S.; El Zein, G. Microwave Doppler Radar for Heartbeat Detection Vs Electrocardiogram. Microw. Opt. Technol. Lett. 2012, 54, 2610–2617. [Google Scholar] [CrossRef]
- Singh, A.; Lubecke, V.; Boric-Lubecke, O. Pulse Pressure Monitoring Through Non-Contact Cardiac Motion Detection Using 2.45 GHz Microwave Doppler Radar. In Proceedings of the 33rd Annual International Conference of the IEEE EMBS, Boston, MA, USA, 30 August–3 September 2011; pp. 4336–4339. [Google Scholar]
- Tran, V.P.; Al-Jumaily, A.A. Non-Contact Real-Time Estimation of Intrapulmonary Pressure and Tidal Volume for Chronic Heart Failure Patients. In Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Orlando, FL, USA, 18 October 2016; pp. 3564–3567. [Google Scholar]
- Massagram, W.; Hafner, N.; Lubecke, V.; Boric-Lubecke, O. Tidal Volume Measurement through Non-Contact Doppler Radar with DC Reconstruction. IEEE Sens. J. 2013, 13, 3397–3404. [Google Scholar] [CrossRef]
- Lee, Y.S.; Pathirana, P.N.; Steinfort, C.L.; Caelli, T. Non-Contact Measurement of Respiratory Function and Deduction of Tidal Volume. In Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, IL, USA, 26–30 August 2014; pp. 594–597. [Google Scholar]
- Chazal, P.D.; Fox, N.; O’Hare, E.; Heneghan, C.; Zaffaroni, A.; Boyle, P.; Smith, S.; O’Connell, C.; McNicholas, W.T. Sleep⁄wake measurement using a non-contact biomotion sensor. J. Sleep Res. 2011, 20, 356–366. [Google Scholar] [CrossRef] [PubMed]
- Zaffaroni, A.; Chazal, P.D.; Heneghan, C.; Boyle, P.; Ronayne, P.; McNicholas, W.T. SleepMinder: An Innovative Contact-Free Device for the Estimation of the Apnoea-Hypopnoea Index. In Proceedings of the 31st Annual International Conference of the IEEE EMBS, Minneapolis, MN, USA, 2–6 September 2009; pp. 7091–7094. [Google Scholar]
- Savage, H.O.; Khushaba, R.; Bateman, P.; Farrugia, S.; Schindhelm, K.; Simonds, A.K.; Cowie, M.R. A Novel Non-Contact Device That Identifies and Categorises Sleep Disordered Breathing in Patients with Chronic Heart Failure. Heart 2013, 99. [Google Scholar] [CrossRef]
- Savage, H.O.; Khushaba, R.; Bateman, P.; Farrugia, S.; Schindhelm, K.; Simonds, A.K.; Cowie, M.R. Cheyne Stokes respiration in patients with heart failure detected by a novel non-contact monitor of nocturnal respiration. Eur. J. Heart Fail. 2013, 12, S1. [Google Scholar]
- Li, Y.; Pal, R.; Li, C. Non-contact Multi-Radar Smart Probing of Body Orientation based on Micro-Doppler Signatures. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2014, 598–601. [Google Scholar] [CrossRef]
- Tran, V.P.; Al-Jumaily, A.A. Non-Contact Doppler Radar Based Prediction of Nocturnal Body Orientations Using Deep Neural Network for Chronic Heart Failure Patients. In Proceedings of the 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA), Ras Al Khaimah, UAE, 21–23 November 2017. [Google Scholar]
- Baldi, M.; Appignani, F.; Zanaj, B.; Chiaraluce, F. Body Movement Compensation in UWB Radars for Respiration Monitoring. In Proceedings of the 2012 IEEE First AESS European Conference on Satellite Telecommunications (ESTEL), Rome, Italy, 2–5 October 2012; pp. 1–6. [Google Scholar]
- Sachs, J.; Helbig, M.; Herrmann, R.; Kmec, M.; Schilling, K.; Zaikov, E. Remote vital sign detection for rescue, security, and medical care by ultra-wideband pseudo-noise radar. Ad Hoc Netw. 2012, 13, 42–53. [Google Scholar] [CrossRef]
- Kiriazi, J.E.; Boric-Lubecke, O.; Lubecke, V. Considerations in Measuring Vital Signs Cross Section with Doppler Radar. In Proceedings of the Radio and Wireless Symposium (RWS 2011), Phoenix, AZ, USA, 16–19 January 2011; pp. 426–429. [Google Scholar]
- Park, B.-K.; Boric-Lubecke, O.; Lubecke, V.M. Arctangent Demodulation With DC Offset Compensation in Quadrature Doppler Radar Receiver Systems. IEEE Trans. Microw. Theory Tech. 2007, 55, 1073–1079. [Google Scholar] [CrossRef]
- Wu, P.-H.; Jau, J.-K.; Li, C.-J.; Horng, T.-S.; Hsu, P. Phase- and Self-Injection-Locked Radar for Detecting Vital Signs with Efficient Elimination of DC Offsets and Null Points. IEEE Trans. Microw. Theory Tech. 2013, 61, 685–695. [Google Scholar] [CrossRef]
- Steffen, M.; Leonhardt, S. Non-Contact Monitoring of Heart and Lung Activity by Magnetic Induction Measurement. Acta Polytech. 2008, 48, 71–78. [Google Scholar]
- Aardal, Ø.; Paichard, Y.; Brovoll, S.; Berger, T.; Lande, T.S.; Hamran, S.-E. Physical Working Principles of Medical Radar. IEEE Trans. Biomed. Eng. 2013, 60, 1142–1149. [Google Scholar] [CrossRef] [PubMed]
- Vasu, V.; Fox, N.; Brabetz, T.; Wren, M.; Heneghan, C.; Sezer, S. Detection of Cardiac Activity using a 5.8 GHz Radio Frequency Sensor. In Proceedings of the 31st Annual International Conference of the IEEE EMBS, Minneapolis, MN, USA, 2–6 September 2009; pp. 4682–4686. [Google Scholar]
- Droitcour, A.D.; Boric-Lubecke, O.; Lubecke, V.M.; Lin, J.; Kovacs, G.T.A. Range Correlation and I/Q Performance Benefits in Single-Chip Silicon Doppler Radars for Noncontact Cardiopulmonary Monitoring. IEEE Trans. Microw. Theory Tech. 2004, 52, 838–847. [Google Scholar] [CrossRef]
- Ichapurapu, R.; Jain, S.; John, G.; Monday, T.; Lie, D.Y.C.; Banister, R.; Griswold, J. A 2.4GHz Non-Contact Biosensor System for Continuous Vital-Signs Monitoring. In Proceedings of the Wireless and Microwave Technology Conference, Clearwater, FL, USA, 20–21 April 2009; pp. 1–3. [Google Scholar]
- Fletcher, R.; Han, J. Low-Cost Differential Front-End for Doppler Radar Vital Sign Monitoring. In Proceedings of the 2009 IEEE MTT-S International Microwave Symposium Digest, Boston, MA, USA, 7–12 June 2009; pp. 1325–1328. [Google Scholar]
- Lu, G.; Yang, F.; Tian, Y.; Jing, X.; Wang, J. Contact-free Measurement of Heart Rate Variability via a Microwave Sensor. Sensors 2009, 9, 9572–9581. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Das, V.; Boothby, A.; Hwang, R.; Nguyen, T.; Lopez, J.; Lie, D.Y.C. Antenna Evaluation of a Non-Contact Vital Signs Sensor for Continuous Heart and Respiration Rate Monitoring. In Proceedings of the Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS 2012), Santa Clara, CA, USA, 15–18 January 2012; pp. 13–16. [Google Scholar]
- Han, J.; Kim, J.-G.; Hong, S. A Compact Ka-Band Doppler Radar Sensor for Remote Human Vital Signal Detection. J. Electromagn. Eng. Sci. 2012, 12, 234–239. [Google Scholar] [CrossRef] [Green Version]
- Boothby, A.; Das, V.; Lopez, J.; Tsay, J.; Nguyen, T.; Banister, R.E.; Lie, D.Y.C. Accurate and Continuous Non-Contact Vital Signs Monitoring Using Phased Array Antennas in a Clutter-Free Anechoic Chamber. In Proceedings of the 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 3–7 July 2013; pp. 2862–2865. [Google Scholar]
- Fletcher, R.R.; Kulkarni, S. Wearable Doppler radar with integrated antenna for patient vital sign monitoring. In Proceedings of the Radio and Wireless Symposium (RWS 2010), New Orleans, LA, USA, 10–14 January 2010; pp. 276–279. [Google Scholar]
- Othman, M.A.; Sinnappa, M.; Azman, H.; Abidin Abd Aziz, M.Z.; Ismail, M.M.; Hussein, M.N.; Sulaiman, H.A.; Misran, M.H.; Meor Said, M.A.; Ramlee, R.A.; et al. 5.8 GHz Microwave Doppler Radar for Heartbeat Detection. In Proceedings of the 23th Conference Radioelektronika, Pardubice, Czech Republic, 16–17 April 2013; pp. 367–370. [Google Scholar]
- An, Y.-J.; Hong, Y.-P.; Jang, B.-J.; Yook, J.-G. Comparative Study of 2.4 GHz and 10 GHz Vital Signal Sensing Doppler Radars. In Proceedings of the 40th European Microwave Conference, Paris, France, 28–30 September 2010; pp. 501–504. [Google Scholar]
- Gao, X.; Singh, A.; Yavari, E.; Lubecke, V.; Boric-Lubecke, O. Non-contact Displacement Estimation Using Doppler Radar. In Proceedings of the 34th Annual International Conference of the IEEE EMBS, San Diego, CA, USA, 28 August–1 September 2012; pp. 1602–1605. [Google Scholar]
- Li, C.; Lin, J. Complex Signal Demodulation and Random Body Movement Cancellation Techniques for Non-contact Vital Sign Detection. In Proceedings of the 2008 IEEE MTT-S International Microwave Symposium Digest, Atlanta, GA, USA, 15–20 June 2008; pp. 567–570. [Google Scholar]
- Rahman, M.S.; Kim, K.-D. Extended Kalman Filter for Rate Estimation in Doppler Radar Cardiopulmonary Monitoring System. Int. J. Bio-Sci. Bio-Technol. 2012, 4, 95–106. [Google Scholar]
- Zhou, Q.; Liu, J.; Høst-Madsen, A.; Boric-Lubecke, O.; Lubecke, V. Detection of Multiple Heartbeats Using Doppler Radar. In Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing, Toulouse, France, 14–19 May 2006; pp. 1160–1163. [Google Scholar]
- Li, C.; Lin, J. Recent Advances in Doppler Radar Sensors for Pervasive Healthcare Monitoring. In Proceedings of the Asia-Pacific Microwave Conference 2010, Yokohama, Japan, 7–10 December 2010; pp. 283–290. [Google Scholar]
- Kiriazi, J.E.; Boric-Lubecke, O.; Lubecke, V.M. Radar Cross Section of Human Cardiopulmonary Activity for Recumbent Subject. In Proceedings of the 31st Annual International Conference of the IEEE EMBS, Minneapolis, MN, USA, 2–6 September 2009; pp. 4808–4811. [Google Scholar]
- Li, C.; Lin, J. Random Body Movement Cancellation in Doppler Radar Vital Sign Detection. IEEE Trans. Microw. Theory Tech. 2008, 56, 3143–3152. [Google Scholar]
- Mostafanezhad, I.; Boric-Lubecke, O.; Lubecke, V.; Mandic, D.P. Application of Empirical Mode Decomposition in Removing Fidgeting Interference in Doppler Radar Life Signs Monitoring Devices. In Proceedings of the 31st Annual International Conference of the IEEE EMBS, Minneapolis, MN, USA, 2–6 September 2009; pp. 340–343. [Google Scholar]
- Chen, Y.; Tan, H.; Hu, B.; Li, Y. Doppler Radar Based Non-Contact Multi-Person Respiration Signals Separation. In Proceedings of the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2012), Hong Kong and Shenzhen, China, 2–7 January 2012; pp. 799–802. [Google Scholar]
- Kazemi, S.; Ghorbani, A.; Amindavar, H.; Li, C. Cyclostationary approach to Doppler radar heart and respiration rates monitoring with body motion cancelation using Radar Doppler System. Biomed. Signal Process. Control 2014, 13, 79–88. [Google Scholar] [CrossRef]
- Qiao, D.; He, T.; Hu, B.; Li, Y. Non-contact physiological signal detection using continuous wave Doppler radar. Bio-Med. Mater. Eng. 2014, 24, 993–1000. [Google Scholar]
- Obeid, D.; Sadek, S.; Zaharia, G.; El Zein, G. Doppler Radar for Heartbeat Rate and Heart Rate Variability Extraction. In Proceedings of the 3rd International Conference on E-Health and Bioengineering, Iaşi, Romania, 24–26 November 2011. [Google Scholar]
- Yavari, E.; Padasdao, B.; Lubecke, V.; Boric-Lubecke, O. Packet Radar Spectrum Recovery for Physiological Signals. In Proceedings of the 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 3–7 July 2013; pp. 1760–1763. [Google Scholar]
- Birsan, N.; Munteanu, D.-P.; Iubu, G.; Niculescu, T. Time-Frequency Analysis in Doppler Radar for Noncontact Cardiopulmonary Monitoring. In Proceedings of the 3rd International Conference on E-Health and Bioengineering—EHB 2011, Iaşi, Romania, 24–26 November 2011; pp. 1–4. [Google Scholar]
- Tu, J.; Lin, J. Respiration Harmonics Cancellation for Accurate Heart Rate Measurement in Non-contact Vital Sign Detection. In Proceedings of the 2013 IEEE MTT-S International Microwave Symposium Digest (IMS), Seattle, WA, USA, 2–7 June 2013; pp. 1–3. [Google Scholar]
- Noguchi, H.; Kubo, H.; Mori, T.; Sato, T.; Sanada, H. Signal Phase Estimation for Measurement of Respiration Waveform Using a Microwave Doppler Sensor. In Proceedings of the 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 3–7 July 2013; pp. 6740–6743. [Google Scholar]
- Rahman, M.S.; Jang, B.-J.; Kim, K.-D. A New Digital Signal Processor for Doppler Radar Cardiopulmonary Monitoring System. In Proceedings of the 5th International Conference on Electrical and Computer Engineering (ICECE 2008), Dhaka, Bangladesh, 20–22 December 2008; pp. 76–79. [Google Scholar]
- Tariq, A.; Shiraz, H.G. Doppler Radar Vital Signs Monitoring using Wavelet Transform. In Proceedings of the 2010 Loughborough Antennas & Propagation Conference, Loughborough, UK, 8–9 November 2010; pp. 293–296. [Google Scholar]
- Hu, W.; Zhang, H.; Zhao, Z.; Wang, Y.; Wang, X. Real-time remote vital sign detection using a portable Doppler sensor system. In Proceedings of the IEEE Sensors Applications Symposium (SAS), Queenstown, New Zealand, 18–20 February 2014; pp. 89–93. [Google Scholar]
- Li, C.; Ling, J.; Li, J.; Lin, J. Accurate Doppler Radar Noncontact Vital Sign Detection Using the RELAX Algorithm. IEEE Trans. Instrum. Meas. 2010, 59, 687–695. [Google Scholar]
- Vasu, V.; Fox, N.; Heneghan, C.; Sezer, S. Using the Lomb Periodogram for Non-Contact Estimation of Respiration Rates. In Proceedings of the 32nd Annual International Conference of the IEEE EMBS, Buenos Aires, Argentina, 31 August–4 September 2010; pp. 2407–2410. [Google Scholar]
- Inui, S.; Okusa, K.; Maeno, K.; Kanakura, T. Recognizing Aspiration Presence using Model Parameter Classification from Microwave Doppler Signals. In Proceedings of the World Congress on Engineering and Computer Science (WCECS 2012), San Francisco, CA, USA, 24–26 October 2012. [Google Scholar]
- Li, J.; Zeng, Z.; Sun, J.; Liu, F. Through-Wall Detection of Human Being’s Movement by UWB Radar. IEEE Geosci. Remote Sens. Lett. 2012, 9, 1079–1083. [Google Scholar] [CrossRef]
- Nijsure, Y.; Tay, W.P.; Gunawan, E.; Wen, F.; Yang, Z.; Guan, Y.L.; Chua, A.P. An Impulse Radio Ultrawideband System for Contactless Noninvasive Respiratory Monitoring. IEEE Trans. Biomed. Eng. 2013, 60, 1509–1517. [Google Scholar] [CrossRef] [PubMed]
- Li, X.; Qiao, D.; Li, Y.; Dai, H. A Novel Through-Wall Respiration Detection Algorithm Using UWB Radar. In Proceedings of the 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, 3–7 July 2013; pp. 1013–1016. [Google Scholar]
- Li, W.Z.; Li, Z.; Lv, H.; Lu, G.H.; Zhang, Y.; Jing, X.J.; Li, S.; Wang, J.Q. A new method for non-line-of-sight vital sign monitoring based on developed adaptive line enhancer using low centre frequency UWB radar. Prog. Electromagn. Res. 2013, 133, 535–554. [Google Scholar] [CrossRef]
- Ascione, M.; Buonanno, A.; D’Urso, M.; Angrisani, L.; LoMoriello, R.S. A New Measurement Method Based on Music Algorithm for Through-the-Wall Detection of Life Signs. IEEE Trans. Instrum. Meas. 2013, 62, 13–26. [Google Scholar] [CrossRef]
- Lazaro, A.; Girbau, D.; Villarino, R. Techniques for Clutter Suppression in the Presence of Body Movements during the Detection of Respiratory Activity through UWB Radars. Sensors 2014, 14, 2595–2618. [Google Scholar] [CrossRef] [Green Version]
Physiological Parameters | Reference |
---|---|
Respiratory rate | [15,35,36,37,38,39,40] |
Heart rate | [14,15,38,39,40] |
Heart rate variability | [41] |
Pulse pressure | [42] |
Intrapulmonary pressure | [43] |
Tidal volume | [43,44,45] |
Sleep/wake pattern | [12,46] |
Apnea-hypopnea index | [17,47,48] |
Cheyne-Stokes Respiration | [49] |
Body orientations | [50,51] |
Physiological Parameters | Achievements | Year & References |
---|---|---|
Respiratory rate | Up to 91.52% accuracy with error up to ±1.31 breaths per minute. | 2010–2015 [15,35,36,37,38,39,40] |
Heart rate | Up to 91.29% accuracy with error up to ±6.16 beats per minute. | 2013–2015 [14,15,38,39,40] |
Heart rate variability | Error between 3–11% for single antenna, and 1–6% for dual antenna. | 2012 [41] |
Pulse pressure | Preliminary observation was made on the correlation between the pulse pressure and cardiac motion. | 2011 [42] |
Intrapulmonary pressure | Demonstrated as feasible through modeling and interrelated to the tidal volume estimation accuracy. | 2016 [43] |
Tidal volume | Up to 83.13% accuracy with error up to 57.32 milliliters. | 2013–2016 [43,44,45] |
Sleep/wake pattern | Up to 69% for awake state and 88% for sleep stages. | 2008 & 2011 [12,46] |
Apnea-hypopnea index | Overall accuracy of 85.8% with 70% sensitivity and 89% specificity. | 2009–2016 [17,47,48] |
Cheyne-Stokes Respiration | Correlation coefficient of 0.87 with %CSR > 5 and 0.8 with AHI > 15. | 2013 [49] |
Body orientations | Overall accuracy of 99.2%. | 2017 [51] |
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Tran, V.P.; Al-Jumaily, A.A.; Islam, S.M.S. Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review. Big Data Cogn. Comput. 2019, 3, 3. https://doi.org/10.3390/bdcc3010003
Tran VP, Al-Jumaily AA, Islam SMS. Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review. Big Data and Cognitive Computing. 2019; 3(1):3. https://doi.org/10.3390/bdcc3010003
Chicago/Turabian StyleTran, Vinh Phuc, Adel Ali Al-Jumaily, and Syed Mohammed Shamsul Islam. 2019. "Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review" Big Data and Cognitive Computing 3, no. 1: 3. https://doi.org/10.3390/bdcc3010003
APA StyleTran, 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. https://doi.org/10.3390/bdcc3010003