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research-article

A visual context-awareness-based sleeping-respiration measurement system

Authors:

Pau-Choo ChungAuthors Info & Claims

IEEE Transactions on Information Technology in Biomedicine, Volume 14, Issue 2

Pages 255 - 265

https://doi.org/10.1109/TITB.2009.2036168

Published: 01 March 2010 Publication History

Abstract

Due to the rapid growth of the elderly population, improving specific aspects of elderly healthcare has become more important. Sleeping care systems for the elderly are rare. In this paper, we propose a visual context-aware-based sleeping-respiration measurement system that measures the respiration information of elderly sleepers. Accurate respiration measurement requires considering all possible contexts for the sleeping person. The proposed system consists of a body-motion-context-detection subsystem, a respiration-context-detection subsystem, and a fast motion-vector-estimation-based respiration measurement subsystem. The system yielded accurate respiratory measurements for our study population.

References

[1]

G. B. Moody, R. G. Mark, A. Zoccola, and S. Mantero, "Derivation of respiratory signals from multi-lead ECGs," Comput. Cardiol., vol. 12, pp. 113-116, 1985.

[2]

G. B. Moody, R. G. Mark, M. A. Bump, J. S. Weinstein, A. D. Berman, J. E. Mietus, and A. L. Goldberger, "Clinical validation of the ECG-derived respiration (EDR) technique," Comput. Cardiol., vol. 13, pp. 507-510, 1986.

[3]

M. Ishijima, "Cardiopulmonary monitoring by textile electrodes without subject-awareness of beingmonitored," Med. Biol. Eng. Comput., vol. 35, pp. 685-690, 1997.

[4]

E. P. Scilingo, A. Gemignani, R. Paradiso, N. Taccini, B. Ghelarducci, and D. De Rossi, "Performance evaluation of sensing fabrics for monitoring physiological and biomechanical variables," IEEE Trans. Inf. Technol. Biomed., vol. 9, no. 3, pp. 345-352, Sep. 2005.

Digital Library

[5]

D. Barschdorff and W. Zhang, "Respiratory rhythm detection with photo-plethysmographic methods," in Proc. 16th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., Eng. Adv.: New Oppor. Biomed. Eng., 1994, vol. 2, pp. 912-913.

[6]

C. Ahlstrom, A. Johansson, T. Lanne, and P. Ask, "A respiration monitor based on electrocardiographic and photoplethysmographic sensor fusion," in Proc. 26th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2004, pp. 2311-2314.

[7]

M. Kermit, A. J. Eide, T. Lindblad, and K. Waldemark, "Treatment of obstructive sleep apnea syndrome by monitoring patient airflow signals," Pattern Recog. Lett., vol. 21, pp. 277-281, 2000.

Digital Library

[8]

B. A. Phillips, M. I. Anstead, and D. J. Gottlieb, "Monitoring sleep and breathing: Methodology. Part I: Monitoring breathing," Clin. Chest Med., vol. 19, no. 1, pp. 203-212, 1998.

[9]

J. R. Stradling, "New approaches to monitoring sleep-related breathing disorders," Sleep, vol. 18, no. 3, pp. 77-84, 1996.

[10]

B. H. Taha, J. A. Dempsey, S. M. Weber, M. S. Badr, J. B. Skatrud, T. B. Young, A. J. Jacques, and K.C. Seow, "Automated detection and classification of sleep-disordered breathing from conventional polysomnography data," Sleep, vol. 20, no. 11, pp. 991-1001, 1997.

[11]

A. Bartolo, B. D. Clymer, J. A. Golish, and R. C. Burgess, "The polysomnogram assay: A method to represent the overnight polysomnogram in a condensed fromat," Comput. Biomed. Res., vol. 33, no. 2, pp. 110-125, 2000.

Digital Library

[12]

R. K. Millard, "Inductive plethysmography components analysis and improved noninvasive postoperative apnoea monitoring," Physiol. Meas., vol. 20, no. 2, pp. 175-186, 1999.

[13]

P. Varady, L. Nagy, and L. Szilagyi, "Online detection of sleep apnea during critical care monitoring," in Proc. 22nd Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2000, vol. 2, pp. 1299-1301.

[14]

P. Várady, T. Micsik, S. Benedek, and Z. Benyó, "A novel method for the detection of apnea and hypopnea events in respiration signals," IEEE Trans. Biomed. Eng., vol. 49, no. 9, pp. 936-942, Sep. 2002.

[15]

K. Nepal, E. Biegeleisen, and T. Ning, "Apnea detection and respiration rate estimation through parametricmodelling," in Proc. IEEE 28th Annu. Northeast Bioeng. Conf., 2002, pp. 277-278.

[16]

M. I. Restrepo, S. Bhandari, and T. Ning, "Classification of respiration episodes using fuzzy logic," in Proc. IEEE 32nd Annu. Northeast Bioeng. Conf., 2006, pp. 133-134.

[17]

H. Kametani, M. Takao, and T. Setoguchi, "Characteristic evaluation of the flowmeter using the Wells turbine for measurement of respiration," in Proc. 41st SICE Annu. Conf. (SICE 2002), vol. 1, pp. 531-534.

[18]

Y. Wang, H. Baghaei, H. Li, Y. Liu, T. Xing, J. Uribe, R. Ramirez, S. Xie, S. Kim, and W.-H. Wong, "A simple respiration gating technique and its application in high-resolution PET camera," IEEE Trans. Nucl. Sci., vol. 52, no. 1, pp. 125-129, Feb. 2005.

[19]

B. W. Carlson, V. J. Neelon, and H. Hsiao, "Evaluation of a noninvasive respiratory monitoring system for sleeping subjects," Physiol. Meas., vol. 20, pp. 53-63, 1999.

[20]

W. Chen, X. Zhu, T. Nemoto, Y. Kanemitsu, K. Kitamura, and K. Yamakoshi, "Unconstrained detection of respiration rhythm and pulse rate with one under-pillow sensor during sleep," Med. Biol. Eng. Comput., vol. 43, pp. 306-312, 2005.

[21]

T. Usui, A. Matsubara, and S. Tanaka, "Unconstrained and noninvasive measurement of heartbeat and respiration using an acoustic sensor enclosed in an air pillow," in Proc. SICE Annu. Conf., 2004, vol. 3, pp. 2648- 2651.

[22]

S. Brady, L. E. Dunne, R. Tynan, D. Diamond, B. Smyth, and G. M. P. O'Hare, "Garment-based monitoring of respiration rate using a foam pressure sensor," in Proc. 9th IEEE Int. Symp. Wearable Comput., 2005, pp. 214-215.

Digital Library

[23]

I. Svetlana, H. Y. Mammo, W. A. John, E. H. Michael, H. M. Carl, and R. P. Scott, "A gated deep inspiration breath-hold radiation therapy technique using a linear position transducer," J. Appl. Clin. Med. Phys., vol. 6, pp. 61-70, 2005.

[24]

The product of company "Hyun Medics" in Korea (South), "Baby breath monitor (Aggabi)." Available: http://hyun.en.ecplaza.net/14.asp

[25]

M. A. Gennert, J. K. Ho, A. C. Quina, J. H. Wang, P. P. Bruyant, and M. A. King, "Feasibility of tracking patient respiration during cardiac SPECT imaging using stereo optical cameras," in Proc. IEEE Nucl. Sci. Symp. Conf. Record, 2003, vol. 5, pp. 3170-3172.

[26]

R. Paradiso, G. Loriga, and N. Taccini, "A wearable health care system based on knitted integrated sensors," IEEE Trans. Inf. Technol. Biomed., vol. 9, no. 3, pp. 337-344, Sep. 2005.

Digital Library

[27]

J. C. Lin, "Noninvasive microwave measurement of respiration," Proc. IEEE, vol. 63, no. 10, pp. 1530-1530, Oct. 1975.

[28]

Y. Huang, K. M. Chen, J. Zhang, and Y. Dai, "Fast accurate measurement of phase and amplitude using EM microprocessor-based zero-balance system," presented at the 4th Int. Symp. Antennas EM Theory, Xi'an, China, Aug. 19-22, 1997.

[29]

Y. Xiao, J. Lin, O. Boric-Lubecke, and V. Lubecke, "A Ka-band low power doppler radar system for remote detection of cardiopulmonary motion," in Proc. 2005 IEEE Eng. Med. Biol. 27th Annu. Conf., Sep. 1-4, pp. 7151-7154.

[30]

N. D. Duffy, S. McGowan, and G. B. Drummond, "Optical noncontact measurement of abdominal volume change during anaesthesia," in Proc. IEE Colloq. Opt. Tech. Biomed. Appl., Jun.14, 1991, pp. 8/1-8/4.

[31]

Z. Zhu, J. Fei, and I. Pavlidis, "Tracking human breath in infrared imaging," in Proc. 5th IEEE Symp. Bioinformatics Bioeng., 2005, pp. 227- 231.

Digital Library

[32]

R. Murthy and I. Pavlidis, "Noncontact measurement of breathing function," IEEE Eng. Med. Biol. Mag., vol. 25, no. 3, pp. 57-67, May-Jun. 2006.

[33]

D. U. Silverthorn, "Respiratory physiology," in Human Physiology: An Integrated Approach, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 2001, pp. 498-508.

[34]

B. K. P. Horn and B. G. Schunck, "Determining optical flow," Artif. Intell., vol. 17, pp. 185-203, 1981.

Digital Library

[35]

K. Fukunaga and L. D. Hostetler, "The estimation of the gradient of a density function, with applications in pattern recognition," IEEE Trans. Inf. Theory, vol. 21, no. 1, pp. 32-40, 1975.

Digital Library

[36]

A. J. Lipton, H. Fujiyoshi, and R. S. Patil, "Moving target classification and tracking from real-time video," in Proc. IEEE Workshop Appl. Comput. Vis., 1998, pp. 8-14.

Digital Library

[37]

N. Friedman and S. Russell, "Image segmentation in video sequences: A probabilistic approach," in Proc. 13th Conf. Uncertainty Artif. intell., 1997, pp. 175-181.

Digital Library

[38]

B.P. L. Lo and S. A. Velastin, "Automatic congestion detection system for underground platforms," in Proc. ISIMP, pp. 158-161, 2001.

[39]

A. Elgammal, R. Duraiswami, D. Harwood, and L. S. Davis, "Background and foreground modeling using nonparametric kernel density estimation for visual surveillance," Proc. IEEE, vol. 90, no. 7, pp. 1151-1163, Jul. 2002.

[40]

C. R. Wren, A. Azarbayejani, T. Darrell, and A. P. Pentland, "Pfinder: Realtime tracking of the human body," IEEE Trans. Pattern Anal. Mach. intell., vol. 19, no. 7, pp. 780-785, Jul. 1997.

Digital Library

[41]

C. Stauffer and W. E. L. Grimson, "Adaptive background mixture models for real-time tracking," in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recog., 1999, vol. 2, pp. 246-252.

[42]

L. E. Baum and T. Petrie, "Statistical inference for probabilistic functions of finite state Markov chains," Ann. Math. Stat., vol. 37, pp. 1554-1563, 1966.

[43]

L. R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proc. IEEE, vol. 77, no. 2, pp. 257-286, Feb. 1989.

Cited By

Bhola GVishwakarma D(2024)A review of vision-based indoor HAR: state-of-the-art, challenges, and future prospectsMultimedia Tools and Applications10.1007/s11042-023-15443-583:1(1965-2005)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s11042-023-15443-5
Mahmud UJaved M(2018)Context Inference Engine (CiE)International Journal of Advanced Pervasive and Ubiquitous Computing10.4018/japuc.20120701024:3(13-41)Online publication date: 16-Dec-2018
https://dl.acm.org/doi/10.4018/japuc.2012070102
Kempfle JVan Laerhoven K(2018)Respiration Rate Estimation with Depth CamerasProceedings of the 5th International Workshop on Sensor-based Activity Recognition and Interaction10.1145/3266157.3266208(1-10)Online publication date: 20-Sep-2018
https://dl.acm.org/doi/10.1145/3266157.3266208

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Published In

cover image IEEE Transactions on Information Technology in Biomedicine

IEEE Transactions on Information Technology in Biomedicine Volume 14, Issue 2

Special section on affective and pervasive computing for healthcare

March 2010

358 pages

ISSN:1089-7771

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Copyright © 2010.

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IEEE Press

Publication History

Published: 01 March 2010

Revised: 04 July 2009

Received: 22 November 2008

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Cited By

Bhola GVishwakarma D(2024)A review of vision-based indoor HAR: state-of-the-art, challenges, and future prospectsMultimedia Tools and Applications10.1007/s11042-023-15443-583:1(1965-2005)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s11042-023-15443-5
Mahmud UJaved M(2018)Context Inference Engine (CiE)International Journal of Advanced Pervasive and Ubiquitous Computing10.4018/japuc.20120701024:3(13-41)Online publication date: 16-Dec-2018
https://dl.acm.org/doi/10.4018/japuc.2012070102
Kempfle JVan Laerhoven K(2018)Respiration Rate Estimation with Depth CamerasProceedings of the 5th International Workshop on Sensor-based Activity Recognition and Interaction10.1145/3266157.3266208(1-10)Online publication date: 20-Sep-2018
https://dl.acm.org/doi/10.1145/3266157.3266208

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