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Air mattress sensor system with balancing tube for unconstrained measurement of respiration and heart beat movements
Open accessAbstract
The cardio-respiratory signal is a fundamental vital sign used for assessment of a patient's status. Additionally, the cardio-respiratory signal provides a great deal of information to healthcare providers wishing to monitor healthy individuals. The air mattress sensor system allows the measurement of the respiration and heart beat movements without the use of a harness or sensor on the subject's body, which eliminates the difficulties these pose for long term measurements. In order to increase the sensitivity, a differential measurement technique between two air cells was used. The concept of a balancing tube between two air cells is suggested in order to increase the robustness against postural changes during the measurements. With this balancing tube, the meaningful frequency range could be selected using a pneumatic method. A mathematical model was constructed and validation experiments were performed for step and sinusoidal input signals. This technique was applied to measurements of respiration and heart beat movements in the supine posture on the bed, which showed potential for applications in sleep analysis, unconstrained healthcare monitoring and neonate monitoring.
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“Body movements, breathing and even cardiac activities can be detected by the volume change of the pneumatic underneath an individual whilst they are lying in bed52–54.”
From The future of sleep health: a data-driven revolution in sleep science and medicine (2020) · cites this paper as [53]
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Automatic ballistocardiogram (BCG) beat detection using a template matching approach
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“X. Zhang is with the Computer Science and Engineering, University of Washington, Seattle, WA 98195 USA (e-mail: xiaoyiz@cs.washington.edu).”
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“…et al 2005, Park et al 2008), a polyvinylidene fluoride piezopolymer sensor (Niizeki et al 2005), a pneumatic sensor (Watanabe and Watanabe 2004, Chee et al 2005), an optical fibre (Nishyama et al 2011) phonocardiographic sensor (Tanaka et al 2002) or a static-charge-sensitive bed (Alihanka et…”
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Unconstrained monitoring of long-term heart and breath rates during sleep
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“There are some other related works using wireless technology (Xu et al., 2007a; Pan, 2008b; Kortelainen and Virkkala, 2007c; Jeung et al., 2004d; Jeung et al., 2005e) or fluid technology (such as water, air) (Zhu et al., 2005a; Chee et al., 2005b) on respiration and heart rate monitoring.”
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A New Sensory Device and Optimal Position for Monitoring HR/RR during Sleep
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“[3] and Shin et al.”
Motoi, K., Ogawa, M., Ueno, H., Fukunaga, S., Yuji, T., Higashi, Y., Tanaka, S., Fujimoto, T., Asanoi, H., & Yamakoshi, K.-I. (2010) · IEEE International Conference on Information Technology and Applications in Biomedicine · doi:10.1109/itab.2010.5687774 · Cited by 8
Sleep and Sleep Assessment Technologies
Koenig, S. M., Mack, D. C., & Alwan, M. (2007) · Humana Press eBooks · doi:10.1007/978-1-59745-233-5_5 · Cited by 8
“Fig. 5.20 Korean Air Mattress [ 91 ] (Image Credit: Used with permission from IOP Publishing Ltd.) 112 S. M. Koenig et al.”
BackgroundMethodInfluentialVital Sign Monitoring for Cancer Patients Based on Dual-Path Sensor and Divided-Frequency-CNN Model
Lin, B., Jia, C., Yang, H., Zhang, Y., Xie, X., Chen, Z., & Zhang, X. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3368061 · Cited by 6
Smartphone-based and non-invasive sleep stage identification system with piezo-capacitive sensors
Pérez-Ávila, A. J., Herrera, N. R., Martínez-Olmos, A., Carvajal, M. A., Capitán-Vallvey, L. F., López-Ruiz, N., & Palma, A. J. (2024) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2024.115659 · Cited by 6
“In recent years, several researchers have advocated for the development of simpler and user-friendly equipment for sleep data recording [11 – 16].”
Tommasi, F. D., D’Antoni, F., Presti, D. L., Silvestri, S., Fortino, G., Schena, E., Merone, M., & Massaroni, C. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3559724 · Cited by 6
“The application of a single airflow sensor in an air pocket single sensor strategically placed into the mattress or placed between the mattress and bedframehasbeeninvestigatedin[39],[40]tomonitorbreathing andcardiacactivities.”
Casanella, R., Khosrow-Khavar, F., Schmidt, S. E., Zanetti, J. M., & Tavakolian, K. (2019) · Series in bioengineering · doi:10.1007/978-981-10-5092-3_3 · Cited by 6
Nonintrusive measurement of biological signals for ubiquitous healthcare
Park, K. S. (2009) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2009.5334000 · Cited by 5
“To solve the saturation problem in air mattress sensor system, balancing tube was used [ 6 ].”
MethodSelf-citationNon-intrusive respiratory monitoring system using Fiber Bragg Grating sensor
Fook, V. F. S., Kng, P. L., Zhong, E., Jayachandran, M., Wai, A. A. P., Biswas, J., Si, L. W., & Yap, P. L. K. (2008) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/health.2008.4600128 · Cited by 5
“The sensors must be sensitive enough to capture the correct respiratory rate while not changing the behavior of the patients or elderly.”
BackgroundPark, K. S., & Yoon, H. (2017) · Springer eBooks · doi:10.1007/978-3-319-69362-0_5 · Cited by 5
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Body Area Network based Health Monitoring of Critical Patients: a Brief Review
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Unobtrusive Non-Contact Detection of Arrhythmias using a “Smart” Bed
Brueser, C. (2011) · Acta Polytechnica · doi:10.14311/1426 · Cited by 3
“Using a variety of different sensors, including but not limited to strain gauges [3, 4], PVDF and EMFi sensors [5, 6], accelerometers [7], hydraulic [8] and pneumatic sensors [9, 10] as well as optical devices [11], BCG systems have been integrated into objects of daily life, such as beds [4–12], chairs [13] and even…”
BackgroundKutílek, P., Zizka, A., & Vítečková, S. (2012) · International Conference on Telecommunications and Signal Processing (TSP) · doi:10.1109/tsp.2012.6256341 · Cited by 3
Apnea Detection with Microbend Fiber-Optic Sensor
Liu, L., Ye, T., Guo, X., Kong, R., Bo, L., & Wang, G. (2017) · Lecture notes in electrical engineering · doi:10.1007/978-981-10-6499-9_21 · Cited by 3
A Machine Learning-Based Non-Contact Respiratory Rate Monitoring Method Using an RGB Camera
Ghodratigohar, M. (2019) · uO Research (University of Ottawa) · doi:10.20381/ruor-23592 · Cited by 3
“Although some contactless methods, namely air mattress sensors, are capable of monitoring respiration [4], the RR signal can be distorted by non-respiratory-induced movements [4].”
BackgroundLin, G., Jia, C., Wang, L., Chen, Z., Yang, H., Lin, X., Liu, T., Chen, W., & Ni, S. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3592200 · Cited by 2
Brüser, C., Strutz, N., Winter, S., Leonhardt, S. K., & Walter, M. (2014) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2014.2340703 · Cited by 2
Kutílek, P., Hozman, J., & Smrčka, P. (2012) · Cited by 2
Tsai, C.-C., Lu, H.-K., Chu, L.-P., Ting, C.-C., Hsieh, K.-C., & Lai, C.-L. (2018) · International Symposium on Computer, Consumer and Control · doi:10.1109/is3c.2018.00031 · Cited by 2
“[5] used an air cushion with an air flow sensor to detect the BCG signal.”
MethodZhang, X., Tang, J., Sharp, G. C., Xiao, L., Xu, S., & Lu, H. (2020) · British Journal of Radiology · doi:10.1259/bjr.20190303 · Cited by 2
Clinical Applications of Behavioral Assessment
Haynes, S. N., Yoshioka, D. T., Kloezeman, K. C., & Bello, I. (2012) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780195366877.013.0013 · Cited by 2
Heart pulse demodulation from Emfit mattress sensor using spectral and source separation techniques.
Perez-Macias, J. M., Värri, A. O., Himanen, S., Tenhunen, M. L., & Viik, J. (2022) · Computing in cardiology · doi:10.22489/cinc.2022.304 · Cited by 2
Pneumatic frequency selection filter in the prior stage of the air pressure transducer
Chee, Y., & Park, K. (2008) · Measurement · doi:10.1016/j.measurement.2008.08.002 · Cited by 1
Self-citationResonant plethysmography for unconstrained monitoring of respiration
Lee, G., & Park, K. S. (2008) · Electronics Letters · doi:10.1049/el:20083125 · Cited by 1
Self-citationBaHammam, A. S., Pandi-Perumal, S. R., & Hunasikatti, M. (2023) · Progress in Sleep Research · doi:10.1007/978-981-99-7901-1_10 · Cited by 1
Noh, Y.-H., & Jeong, D. (2009) · International Conference on Information Sciences and Interaction Sciences · doi:10.1145/1655925.1656019 · Cited by 1
“This make the research of ballistic measurement system is accomplished [5], [6].”
BackgroundA Preliminary Study for Unconstrained Pulse Arrival Time (PAT) Measurement on a Chair
Kim, K. K., Chee, Y., Park, J., Kim, J., Lim, Y. K., & Park, K. S. (2005) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2005.1617253 · Cited by 1
“The PAT can be measured from the electrically non-contact ECG [3], [4] and the pressure pulse of femoral artery with the air cushion using the balancing tubes [5] on a chair.”
MethodSelf-citationMalakuti, K. (2008) · UVic’s Research and Learning Repository (University of Victoria) · Cited by 1
Nanowire and Fiber Composite Electromechanical Sensor
Chen, Q. (2012) · D-Scholarship@Pitt (University of Pittsburgh)
Waters, J. (2011) · University of New Hampshire Scholars Repository (University of New Hampshire at Manchester)
Metadata
- Authors
- Chee, Y., Han, J., Youn, J., & Park, K.
- Affiliations
- Seoul National University (KR)
- ORCID
- Park, Kwangsuk
- Venue
- Physiological Measurement
- Publisher
- IOP Publishing
- Published
- 2005-04-11
- Volume
- 26
- Issue
- 4
- Pages
- 413-422
- ISSN
- 0967-3334 (ISSN-L)
- 1361-6579
- OpenAlex
- W2056344526
- Semantic Scholar
- c5e2afd42dd3b887f73cfd6e7596e5f6829ee799
- Cited by
- 111
- References
- 11
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 4 · 2023: 3 · 2022: 10 · 2021: 3 · 2020: 6 · 2019: 5 · 2018: 7 · 2017: 7 · 2016: 4 · 2015: 3 · 2014: 8 · 2013: 3 · 2012: 10
- FWCI
- 4.19
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Physiological Measurement (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Korea Science and Engineering Foundation
- Arizona Biomedical Research Commission
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Surgery › Hemodynamic Monitoring and Therapy
- Keywords
- respiratory monitoring, cardiorespiratory signals, differential measurement, mathematical model, sleep analysis
- MeSH terms
- Air, Beds, Computer Simulation, Diagnosis, Computer-Assisted, Equipment Design, Heart Rate, Humans, Models, Biological, Monitoring, Physiologic, Respiration, Rheology, Transducers, Equipment Failure Analysis
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