Patient classification based on pre-hospital heart rate variability

IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS

Volumn , Issue , 2008, Pages 125-128

  Padmanabhan, Pavitra ^a   Lin, Zhiping ^b   Huang, Guang Bin ^b   Ong, Marcus Eng Hock ^a  

^a SINGAPORE GENERAL HOSPITAL   (Singapore)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION TECHNIQUES; CRITICALLY-ILL PATIENTS; EMERGENCY DEPARTMENTS; EXTREME LEARNING MACHINES; HEART RATE VARIABILITIES; NON-INVASIVE MEASUREMENTS; PREDICTIVE ABILITIES; VITAL SIGNS;

BACKPROPAGATION; ELECTROCARDIOGRAPHY; HOSPITALS; NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

HEART VALVE PROSTHESES;

EID: 62949195721     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/APCCAS.2008.4745976     Document Type: Conference Paper

References (12)

1. "Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology," Eur. Heart J., vol. 17, pp. 354-81, 1996.
2. S. Cerutti, A. L. Goldberger, and Y. Yamamoto, "Recent advances in heart rate variability signal processing and interpretation," IEEE Trans. Biomed. Eng., Special issue: Recent Advances in Heart Rate Variability Signal Processing and Interpretation, vol. 53, pp. 1-3, 2006.
3. P. Mariani, M. U. Saeed, A. Potti, B. Hebert, K. Sholes, M. J. Lewis, and J. F. Hanley, "Ineffectiveness of the measurement of 'routine' vital signs for adult inpatients with community-acquired pneumonia," Int. J. Nurs. Pract., vol. 12, pp. 105-109, 2006.
4. B. U. Kohler, C. Hennig, and R. Orglmeister, "The principles of software QRS detection," IEEE Eng. Med. Biol. Mag., vol. 21, pp. 42-57, 2002.
5. P. Padmanabhan, Z. Lin, M. E. H. Ong, W. Ser, and G.-B. Huang, "Automatic extraction of HRV sequences from noisy ECG data for reliable analysis and telediagnosis," Proc. 3rd IASTED Int. Conf. Telehealth, pp. 120-3, 2007.
6. T. Mitchell, Machine learning: McGraw-Hill, 1997.
7. G. B. Huang, Q. Y. Zhu, and C. K. Siew, "Extreme learning machine: Theory and applications," Neurocomputing, vol. 70, pp. 489-501, 2006.
8. V. Vapnik, "The Support Vector method," in Artificial Neural Networks - ICANN'97, 1997, pp. 261-271.
9. C.-C. Chang and C.-J. Lin, "LIBSVM: a library for support vector machines,";; available; at:; http://www.csie.ntu.edu.tw/~cjlin/libsvm,2001.
10. P. E. Leaverton, A review of biostatistics : a program for self- instruction, 2nd ed. Boston Little, Brown, 1978., 1978.
11. C.-W. Hsu, C.-C. Chang, and C.-J. Lin, "A Practical Guide to Support Vector Classification," Technical Report. Department of Computer Science and Information Engineering, National Taiwan University,Taipei. http://www.csie.ntu.edu.tw/~cjlin/libsvm/, 2003.
12. J. Haaksma, W. A. Dijk, J. Brouwer, and M. P. van den Berg, "The influence of recording length on time and frequency domain analysis of heart rate variability," Comput. Cardiol., vol. 25, pp. 377-380, 1998.