Analysis of exercise ventilation with autoregressive model and Hilbert-Huang transform

Hsueh Ting Chu; Tieh Cheng Fu

doi:10.3233/978-1-61499-484-8-185

Analysis of exercise ventilation with autoregressive model and Hilbert-Huang transform

Hsueh Ting Chu^*
, Tieh Cheng Fu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

In this study, we propose a method for the quantitative analysis of exercise ventilation signal that is an important diagnostic tool to evaluate the prognosis of chronic heart failure (CHF) patients. An autoregressive (AR) model is used to filter the breath-by-breath measurement of ventilation. Then the signals before reaching the most ventilation are decomposed into intrinsic mode functions (IMF) by Hilbert-Huang transform (HHT). The average amplitude of the second IMF component AmpC2 is used as an indicator about pulmonary function for chronic heart failure patients.

Original language	English
Title of host publication	Intelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014
Editors	William Cheng-Chung Chu, Han-Chieh Chao, Stephen Jenn-Hwa Yang
Publisher	IOS Press BV
Pages	185-192
Number of pages	8
ISBN (Electronic)	9781614994831
DOIs	https://doi.org/10.3233/978-1-61499-484-8-185
State	Published - 2015
Externally published	Yes
Event	International Computer Symposium, ICS 2014 - Taichung, Taiwan Duration: 12 12 2014 → 14 12 2014

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	274
ISSN (Print)	0922-6389
ISSN (Electronic)	1879-8314

Conference

Conference	International Computer Symposium, ICS 2014
Country/Territory	Taiwan
City	Taichung
Period	12/12/14 → 14/12/14

Bibliographical note

Publisher Copyright:
© 2015 The authors and IOS Press. All rights reserved.

Keywords

Hilbert-Huang transform
autoregressive model
periodic breathing
ventilation analysis

Access to Document

10.3233/978-1-61499-484-8-185

Cite this

Chu, H. T., & Fu, T. C. (2015). Analysis of exercise ventilation with autoregressive model and Hilbert-Huang transform. In W. C.-C. Chu, H.-C. Chao, & S. J.-H. Yang (Eds.), Intelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014 (pp. 185-192). (Frontiers in Artificial Intelligence and Applications; Vol. 274). IOS Press BV. https://doi.org/10.3233/978-1-61499-484-8-185

Chu, Hsueh Ting ; Fu, Tieh Cheng. / Analysis of exercise ventilation with autoregressive model and Hilbert-Huang transform. Intelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014. editor / William Cheng-Chung Chu ; Han-Chieh Chao ; Stephen Jenn-Hwa Yang. IOS Press BV, 2015. pp. 185-192 (Frontiers in Artificial Intelligence and Applications).

@inproceedings{a9d91903678548b59954b1b24ce9b418,

title = "Analysis of exercise ventilation with autoregressive model and Hilbert-Huang transform",

abstract = "In this study, we propose a method for the quantitative analysis of exercise ventilation signal that is an important diagnostic tool to evaluate the prognosis of chronic heart failure (CHF) patients. An autoregressive (AR) model is used to filter the breath-by-breath measurement of ventilation. Then the signals before reaching the most ventilation are decomposed into intrinsic mode functions (IMF) by Hilbert-Huang transform (HHT). The average amplitude of the second IMF component AmpC2 is used as an indicator about pulmonary function for chronic heart failure patients.",

keywords = "Hilbert-Huang transform, autoregressive model, periodic breathing, ventilation analysis",

author = "Chu, \{Hsueh Ting\} and Fu, \{Tieh Cheng\}",

year = "2015",

doi = "10.3233/978-1-61499-484-8-185",

language = "英语",

series = "Frontiers in Artificial Intelligence and Applications",

publisher = "IOS Press BV",

pages = "185--192",

editor = "Chu, \{William Cheng-Chung\} and Han-Chieh Chao and Yang, \{Stephen Jenn-Hwa\}",

booktitle = "Intelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014",

address = "荷兰",

}

Chu, HT & Fu, TC 2015, Analysis of exercise ventilation with autoregressive model and Hilbert-Huang transform. in WC-C Chu, H-C Chao & SJ-H Yang (eds), Intelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014. Frontiers in Artificial Intelligence and Applications, vol. 274, IOS Press BV, pp. 185-192, International Computer Symposium, ICS 2014, Taichung, Taiwan, 12/12/14. https://doi.org/10.3233/978-1-61499-484-8-185

Analysis of exercise ventilation with autoregressive model and Hilbert-Huang transform. / Chu, Hsueh Ting; Fu, Tieh Cheng.
Intelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014. ed. / William Cheng-Chung Chu; Han-Chieh Chao; Stephen Jenn-Hwa Yang. IOS Press BV, 2015. p. 185-192 (Frontiers in Artificial Intelligence and Applications; Vol. 274).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this study, we propose a method for the quantitative analysis of exercise ventilation signal that is an important diagnostic tool to evaluate the prognosis of chronic heart failure (CHF) patients. An autoregressive (AR) model is used to filter the breath-by-breath measurement of ventilation. Then the signals before reaching the most ventilation are decomposed into intrinsic mode functions (IMF) by Hilbert-Huang transform (HHT). The average amplitude of the second IMF component AmpC2 is used as an indicator about pulmonary function for chronic heart failure patients.

KW - Hilbert-Huang transform

KW - autoregressive model

KW - periodic breathing

KW - ventilation analysis

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PB - IOS Press BV

T2 - International Computer Symposium, ICS 2014

Y2 - 12 December 2014 through 14 December 2014

ER -

Analysis of exercise ventilation with autoregressive model and Hilbert-Huang transform

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