NDLI: Development of statistical regression models for ventilation estimation

Content Provider	IEEE Xplore Digital Library
Author	Shaopeng Liu Gao, R.X. Qingbo He Staudenmayer, J. Freedson, P.
Copyright Year	2009
Description	Author affiliation: Department of Mathematics and Statistics (Staudenmayer, J.) \|\| Exercise Physiology Laboratory, University of Massachusetts Amherst, Amherst, MA 01003, USA (Freedson, P.) \|\| Electromechanical Systems Laboratory, University of Connecticut, Storrs, CT 06269 (Shaopeng Liu; Gao, R.X.; Qingbo He)
Abstract	Estimation of ventilation volume from dimensional changes of the rib cage and abdomen is of interest to researchers interested in quantifying internal exposure to environmental pollutants in the atmosphere. In this paper, we present different statistical regression models for estimating ventilation volume during free-living activities. The movements of the rib cage and abdomen were measured by piezoelectric sensor belts. Multiple linear regression as the calibration method was applied. Five regression models with different combinations out of thirteen features were developed and the performance of these models was compared through experimental study of 11 subjects. The effect of training approaches — model trained for each subject and for all subjects, and the effect of time intervals for computing features were also investigated. The results indicate that Model 2, combining respiratory features and breathing frequency, with a longer time intervals will lead to a higher accuracy.
Starting Page	1266
Ending Page	1269
File Size	538690
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5333890
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ventilation Atmospheric modeling Abdomen Atmosphere Atmospheric measurements Pollution measurement Belts Linear regression Calibration Frequency
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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