Research progress on the application of novel sensing technologies for sleep-related breathing disorder monitoring at home_Journal of Biomedical Engineering

Authors：

WU Yonglin ¹ ,  CHEN Chen ² , HAN Fang ³ , CHEN Wei ^1,2

1. School of Information Science and Technology, Fudan University, Shanghai 200438, P.R. China;
2. Human Phenome Institute, Fudan University, Shanghai 201203, P.R. China;
3. Department of Respiratory and Critical Care Medicine, People’s Hospital, Peking University, Beijing 100044, P.R. China;

Corresponding author：

CHEN Chen, Email: chenchen_fd@fudan.edu.cn

Keywords：

New sensing technology; Artificial Intelligence; Sleep-related breathing disorder; Sleep apnea-hypopnea syndrome; Wearable device; Unconstrained device; Home health monitor

DOI：

10.7507/1001-5515.202112066

Video：

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Abstract Full text Figures/Tables Video References Cited by

Sleep-related breathing disorder (SRBD) is a sleep disease with high incidence and many complications. However, patients are often unaware of their sickness. Therefore, SRBD harms health seriously. At present, home SRBD monitoring equipment is a popular research topic to help people get aware of their health conditions. This article fully compares recent state-of-art research results about home SRBD monitors to clarify the advantages and limitations of various sensing techniques. Furthermore, the direction of future research and commercialization is pointed out. According to the system design, novel home SRBD monitors can be divided into two types: wearable and unconstrained. The two types of monitors have their own advantages and disadvantages. The wearable devices are simple and portable, but they are not comfortable and durable enough. Meanwhile, the unconstrained devices are more unobtrusive and comfortable, but the supporting algorithms are complex to develop. At present, researches are mainly focused on system design and performance evaluation, while high performance algorithm and large-scale clinical trial need further research. This article can help researchers understand state-of-art research progresses on SRBD monitoring quickly and comprehensively and inspire their research and innovation ideas. Additionally, this article also summarizes the existing commercial sleep respiratory monitors, so as to promote the commercialization of novel home SRBD monitors that are still under research.

Citation： WU Yonglin, CHEN Chen, HAN Fang, CHEN Wei. Research progress on the application of novel sensing technologies for sleep-related breathing disorder monitoring at home. Journal of Biomedical Engineering, 2022, 39(4): 798-805. doi: 10.7507/1001-5515.202112066 Copy

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7.	Fan W, He Q, Meng K, et al. Machine-knitted washable sensor array textile for precise epidermal physiological signal monitoring. Sci Adv, 2020, 6(11): eaay2840.
8.	Roudjane M, Bellemare-Rousseau S, Drouin E, et al. Smart t-shirt based on wireless communication spiral fiber sensor array for real-time breath monitoring: validation of the technology. IEEE Sens J, 2020, 20(18): 10841-10850.
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11.	Nabavi S, Bhadra S. Smart mandibular advancement device for intraoral monitoring of cardiorespiratory parameters and sleeping postures. IEEE Trans Biomed Circuits Syst, 2021, 15(2): 248-258.
12.	Lazaro J, Reljin N, Bailon R, et al. Electrocardiogram derived respiratory rate using a wearable armband. IEEE Trans Biomed Eng, 2021, 68(3): 1056-1065.
13.	Surrel G, Aminifar A, Rincon F, et al. Online obstructive sleep apnea detection on medical wearable sensors. IEEE Trans Biomed Circuits Syst, 2018, 12(4): 762-773.
14.	Alam R, Peden D B, Lach J C. Wearable respiration monitoring: interpretable inference with context and sensor biomarkers. IEEE J Biomed Health Inform, 2021, 25(6): 1938-1948.
15.	Kontaxis S, Lazaro J, Corino V, et al. ECG-derived respiratory rate in atrial fibrillation. IEEE Trans Biomed Eng, 2020, 67(3): 905-914.
16.	Shen Qi, Qin Hengji, Wei Keming, et al. Multiscale deep neural network for obstructive sleep apnea detection using RR interval from single-lead ECG signal. IEEE Trans Instrum Meas, 2021, 70: 2506913.
17.	Ye Guanhua, Yin Hongzhi, Chen Tong, et al. FENet: a frequency extraction network for obstructive sleep apnea detection. IEEE J Biomed Health Inform, 2021, 25(8): 2848-2856.
18.	Faust O, Barika R, Shenfield A, et al. Accurate detection of sleep apnea with long short-term memory network based on rr interval signals. Knowledge-Based Systems, 2021, 212: 106591.
19.	Feng Kaicheng, Qin Hengji, Wu Shan, et al. A sleep apnea detection method based on unsupervised feature learning and Single-Lead electrocardiogram. IEEE Trans Instrum Meas, 2021, 70: 4000912.
20.	Park S, Choi H H, Yang H C, et al. Force-sensing-based unobtrusive system for awakening and respiration rate analysis during sleep. IEEE Sens J, 2019, 19(5): 1917-1924.
21.	Azimi H, Bouchard M, Goubran R, et al. Unobtrusive screening of central sleep apnea from pressure sensors measurements: a patient-specific longitudinal study. IEEE Trans Instrum Meas, 2020, 69(6): 3282-3296.
22.	Matar G, Kaddoum G, Carrier J, et al. Kalman filtering for posture-adaptive in-bed breathing rate monitoring using bed-sheet pressure sensors. IEEE Sens J, 2021, 21(13): 14339-14351.
23.	Zhou Z, Padgett S, Cai Z, et al. Single-layered ultra-soft washable smart textiles for all-around ballistocardiograph, respiration, and posture monitoring during sleep. Biosens Bioelectron, 2020, 155: 112064.
24.	Peng Shun, Xu Ke, Bao Shenjie, et al. Flexible electrodes-based smart mattress for monitoring physiological signals of heart and autonomic nerves in a non-contact way. IEEE Sens J, 2021, 21(1): 6-15.
25.	Sun Chenglu, Li Wei, Chen Chen, et al. An unobtrusive and non-contact method for respiratory measurement with respiratory region detecting algorithm based on depth images. IEEE Access, 2019, 7: 8300-8315.
26.	Rehouma H, Noumeir R, Essouri S, et al. Quantitative assessment of spontaneous breathing in children: evaluation of a depth camera system. IEEE Trans Instrum Meas, 2020, 69(7): 4955-4967.
27.	Wang Tianben, Zhang Daqing, Wang Leye, et al. Contactless respiration monitoring using ultrasound signal with off-the-shelf audio devices. IEEE Internet Things J, 2019, 6(2): 2959-2973.
28.	van Gastel M, Stuijk S, Overeem S, et al. Camera-based vital signs monitoring during sleep - a proof of concept study. IEEE J Biomed Health Inform, 2021, 25(5): 1409-1418.
29.	Deng Fei, Dong Jianwu, Wang Xiangyu, et al. Design and implementation of a noncontact sleep monitoring system using infrared cameras and motion sensor. IEEE Trans Instrum Meas, 2018, 67(7): 1555-1563.
30.	Scebba G, Da Poian G, Karlen W. Multispectral video fusion for non-contact monitoring of respiratory rate and apnea. IEEE Trans Biomed Eng, 2021, 68(1): 350-359.
31.	Zhang Feng, Wu Chenshu, Wang Beibei, et al. SMARS: sleep monitoring via ambient radio signals. IEEE Trans Mob Comput, 2021, 20(1): 217-231.
32.	Yang X, Fan D, Ren A, et al. Sleep apnea syndrome sensing at c-band. IEEE J Transl Eng Health Med, 2018, 6: 2701008.
33.	Hung W P, Chang C H, Lee T H. Real-time and noncontact impulse radio radar system for μm movement accuracy and vital-sign monitoring applications. IEEE Sens J, 2017, 17(8): 2349-2358.
34.	Su W C, Tang M C, Arif R E, et al. Stepped-Frequency continuous-wave radar with self-injection-locking technology for monitoring multiple human vital signs. IEEE Trans Microw Theory Tech, 2019, 67(12): 5396-5405.
35.	Harikesh, Chauhan S S, Basu A, et al. Through the wall human subject localization and respiration rate detection using multichannel doppler radar. IEEE Sens J, 2021, 21(2): 1510-1518.
36.	Gao Qinghua, Tong Jingyu, Wang Jie, et al. Device-free multi-person respiration monitoring using WiFi. IEEE Trans Veh Technol, 2020, 69(11): 14083-14087.
37.	Gottlieb M, Sansom S, Frankenberger C, et al. Clinical course and factors associated with hospitalization and critical illness among COVID-19 patients in Chicago, Illinois. Acad Emerg Med, 2020, 27(10): 963-973.
38.	Mcsharry D, Malhotra A. Potential influences of obstructive sleep apnea and obesity on COVID-19 severity. J Clin Sleep Med, 2020, 16(9): 1645.
39.	Bubu O M, Andrade A G, Umasabor-Bubu O Q, et al. Obstructive sleep apnea, cognition and Alzheimer's disease: a systematic review integrating three decades of multidisciplinary research. Sleep Med Rev, 2020, 50: 101250.

1. Gottlieb D J, Punjabi N M. Diagnosis and management of obstructive sleep apnea: a review. JAMA, 2020, 323(14): 1389-1400.
2. 麻琛彬, 徐浩然, 李德玉. 穿戴式生理参数监测及其I临床应用研究进展. 生物医学工程学杂志, 2021, 38(3): 583-593.
3. Zhang Haodong, Zhang Penglei, Li Yahui, et al. A wearable ultrathin flexible sensor inserted into nasal cavity for precise sleep respiratory monitoring. IEEE Trans Electron Devices, 2021, 68(8): 4090-4097.
4. van Steenkiste T, Groenendaal W, Dreesen P, et al. Portable detection of apnea and hypopnea events using bio-impedance of the chest and deep learning. IEEE J Biomed Health Inform, 2020, 24(9): 2589-2598.
5. Lo Presti D, Massaroni C, D’abbraccio J, et al. Wearable system based on flexible FBG for respiratory and cardiac monitoring. IEEE Sens J, 2019, 19(17): 7391-7398.
6. Lin Y Y, Wu H T, Hsu C A, et al. Sleep apnea detection based on thoracic and abdominal movement signals of wearable piezo-electric bands. IEEE J Biomed Health Inform, 2016, 21(6): 1533-1545.
7. Fan W, He Q, Meng K, et al. Machine-knitted washable sensor array textile for precise epidermal physiological signal monitoring. Sci Adv, 2020, 6(11): eaay2840.
8. Roudjane M, Bellemare-Rousseau S, Drouin E, et al. Smart t-shirt based on wireless communication spiral fiber sensor array for real-time breath monitoring: validation of the technology. IEEE Sens J, 2020, 20(18): 10841-10850.
9. Meng K, Zhao S, Zhou Y, et al. A wireless textile-based sensor system for self-powered personalized health care. Matter, 2020, 2(4): 896-907.
10. Singh S, Kozlowski M, Garcia-Lopez I, et al. Proof of concept of a novel neck-situated wearable PPG system for continuous physiological monitoring. IEEE Trans Instrum Meas, 2021, 70: 9509609.
11. Nabavi S, Bhadra S. Smart mandibular advancement device for intraoral monitoring of cardiorespiratory parameters and sleeping postures. IEEE Trans Biomed Circuits Syst, 2021, 15(2): 248-258.
12. Lazaro J, Reljin N, Bailon R, et al. Electrocardiogram derived respiratory rate using a wearable armband. IEEE Trans Biomed Eng, 2021, 68(3): 1056-1065.
13. Surrel G, Aminifar A, Rincon F, et al. Online obstructive sleep apnea detection on medical wearable sensors. IEEE Trans Biomed Circuits Syst, 2018, 12(4): 762-773.
14. Alam R, Peden D B, Lach J C. Wearable respiration monitoring: interpretable inference with context and sensor biomarkers. IEEE J Biomed Health Inform, 2021, 25(6): 1938-1948.
15. Kontaxis S, Lazaro J, Corino V, et al. ECG-derived respiratory rate in atrial fibrillation. IEEE Trans Biomed Eng, 2020, 67(3): 905-914.
16. Shen Qi, Qin Hengji, Wei Keming, et al. Multiscale deep neural network for obstructive sleep apnea detection using RR interval from single-lead ECG signal. IEEE Trans Instrum Meas, 2021, 70: 2506913.
17. Ye Guanhua, Yin Hongzhi, Chen Tong, et al. FENet: a frequency extraction network for obstructive sleep apnea detection. IEEE J Biomed Health Inform, 2021, 25(8): 2848-2856.
18. Faust O, Barika R, Shenfield A, et al. Accurate detection of sleep apnea with long short-term memory network based on rr interval signals. Knowledge-Based Systems, 2021, 212: 106591.
19. Feng Kaicheng, Qin Hengji, Wu Shan, et al. A sleep apnea detection method based on unsupervised feature learning and Single-Lead electrocardiogram. IEEE Trans Instrum Meas, 2021, 70: 4000912.
20. Park S, Choi H H, Yang H C, et al. Force-sensing-based unobtrusive system for awakening and respiration rate analysis during sleep. IEEE Sens J, 2019, 19(5): 1917-1924.
21. Azimi H, Bouchard M, Goubran R, et al. Unobtrusive screening of central sleep apnea from pressure sensors measurements: a patient-specific longitudinal study. IEEE Trans Instrum Meas, 2020, 69(6): 3282-3296.
22. Matar G, Kaddoum G, Carrier J, et al. Kalman filtering for posture-adaptive in-bed breathing rate monitoring using bed-sheet pressure sensors. IEEE Sens J, 2021, 21(13): 14339-14351.
23. Zhou Z, Padgett S, Cai Z, et al. Single-layered ultra-soft washable smart textiles for all-around ballistocardiograph, respiration, and posture monitoring during sleep. Biosens Bioelectron, 2020, 155: 112064.
24. Peng Shun, Xu Ke, Bao Shenjie, et al. Flexible electrodes-based smart mattress for monitoring physiological signals of heart and autonomic nerves in a non-contact way. IEEE Sens J, 2021, 21(1): 6-15.
25. Sun Chenglu, Li Wei, Chen Chen, et al. An unobtrusive and non-contact method for respiratory measurement with respiratory region detecting algorithm based on depth images. IEEE Access, 2019, 7: 8300-8315.
26. Rehouma H, Noumeir R, Essouri S, et al. Quantitative assessment of spontaneous breathing in children: evaluation of a depth camera system. IEEE Trans Instrum Meas, 2020, 69(7): 4955-4967.
27. Wang Tianben, Zhang Daqing, Wang Leye, et al. Contactless respiration monitoring using ultrasound signal with off-the-shelf audio devices. IEEE Internet Things J, 2019, 6(2): 2959-2973.
28. van Gastel M, Stuijk S, Overeem S, et al. Camera-based vital signs monitoring during sleep - a proof of concept study. IEEE J Biomed Health Inform, 2021, 25(5): 1409-1418.
29. Deng Fei, Dong Jianwu, Wang Xiangyu, et al. Design and implementation of a noncontact sleep monitoring system using infrared cameras and motion sensor. IEEE Trans Instrum Meas, 2018, 67(7): 1555-1563.
30. Scebba G, Da Poian G, Karlen W. Multispectral video fusion for non-contact monitoring of respiratory rate and apnea. IEEE Trans Biomed Eng, 2021, 68(1): 350-359.
31. Zhang Feng, Wu Chenshu, Wang Beibei, et al. SMARS: sleep monitoring via ambient radio signals. IEEE Trans Mob Comput, 2021, 20(1): 217-231.
32. Yang X, Fan D, Ren A, et al. Sleep apnea syndrome sensing at c-band. IEEE J Transl Eng Health Med, 2018, 6: 2701008.
33. Hung W P, Chang C H, Lee T H. Real-time and noncontact impulse radio radar system for μm movement accuracy and vital-sign monitoring applications. IEEE Sens J, 2017, 17(8): 2349-2358.
34. Su W C, Tang M C, Arif R E, et al. Stepped-Frequency continuous-wave radar with self-injection-locking technology for monitoring multiple human vital signs. IEEE Trans Microw Theory Tech, 2019, 67(12): 5396-5405.
35. Harikesh, Chauhan S S, Basu A, et al. Through the wall human subject localization and respiration rate detection using multichannel doppler radar. IEEE Sens J, 2021, 21(2): 1510-1518.
36. Gao Qinghua, Tong Jingyu, Wang Jie, et al. Device-free multi-person respiration monitoring using WiFi. IEEE Trans Veh Technol, 2020, 69(11): 14083-14087.
37. Gottlieb M, Sansom S, Frankenberger C, et al. Clinical course and factors associated with hospitalization and critical illness among COVID-19 patients in Chicago, Illinois. Acad Emerg Med, 2020, 27(10): 963-973.
38. Mcsharry D, Malhotra A. Potential influences of obstructive sleep apnea and obesity on COVID-19 severity. J Clin Sleep Med, 2020, 16(9): 1645.
39. Bubu O M, Andrade A G, Umasabor-Bubu O Q, et al. Obstructive sleep apnea, cognition and Alzheimer's disease: a systematic review integrating three decades of multidisciplinary research. Sleep Med Rev, 2020, 50: 101250.

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Research progress on the application of novel sensing technologies for sleep-related breathing disorder monitoring at home

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