Principal component based system identification and its application to the study of cardiovascular regulation
Includes bibliographical references (p. 197-212).
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2006
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| Online Access: | http://hdl.handle.net/1721.1/34202 |
| _version_ | 1811091155656376320 |
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| author | Xiao, Xinshu |
| author2 | Richard J. Cohen. |
| author_facet | Richard J. Cohen. Xiao, Xinshu |
| author_sort | Xiao, Xinshu |
| collection | MIT |
| description | Includes bibliographical references (p. 197-212). |
| first_indexed | 2024-09-23T14:57:53Z |
| format | Thesis |
| id | mit-1721.1/34202 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T14:57:53Z |
| publishDate | 2006 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/342022019-04-12T23:31:18Z Principal component based system identification and its application to the study of cardiovascular regulation Xiao, Xinshu Richard J. Cohen. Harvard University--MIT Division of Health Sciences and Technology. Harvard University--MIT Division of Health Sciences and Technology. Harvard University--MIT Division of Health Sciences and Technology. Includes bibliographical references (p. 197-212). Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2004. (cont.) Our methods analyze the coupling between instantaneous lung volume and heart rate and, subsequently, derive representative indices of parasympathetic and sympathetic control based on physiological and experimental findings. The validity of each method is evaluated via experimental data collected following interventions with known effect on the parasympathetic or sympathetic control. With the above techniques, this thesis explores an important topic in the field of space medicine: effects of simulated microgravity on cardiac autonomic control and orthostatic intolerance (OI). Experimental data from a prolonged bed rest study (simulation of microgravity condition) are analyzed and the conclusions are: 1) prolonged bed rest may impair autonomic control of heart rate; 2) orthostatic intolerance after bed rest is associated with impaired sympathetic responsiveness; 3) there may be a pre-bed rest predisposition to the development of OI after bed rest. These findings may have significance for studying Earth-bound orthostatic hypotension as well as for designing effective countermeasures to post-flight OI. In addition, they also indicate the efficacy of our proposed methods for autonomic function quantification. System identification is an effective approach for the quantitative study of physiologic systems. It deals with the problem of building mathematical models based on observed data and enables a dynamical characterization of the underlying physiologic mechanisms specific to the individual being studied. In this thesis, we develop and validate a new linear time-invariant system identification approach which is based on a weighted-principal component regression (WPCR) method. An important feature of this approach is its asymptotic frequency-selective property in solving time-domain parametric system identification problems. Owing to this property, data-specific candidate models can be built by considering the dominant frequency components inherent in the input (and output) signals, which is advantageous when the signals are colored, as are most physiologic signals. The efficacy of this method in modeling open-loop and closed-loop systems is demonstrated with respect to simulated and experimental data. In conjunction with the WPCR-based system identification approach, we propose new methods to noninvasively quantify cardiac autonomic control. Such quantification is important in understanding basic pathophysiological mechanisms or in patient monitoring, treatment design and follow-up. by Xinshu Xiao. Ph.D. 2006-09-28T15:17:55Z 2006-09-28T15:17:55Z 2004 2004 Thesis http://hdl.handle.net/1721.1/34202 70046756 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 212 p. 11487628 bytes 11478692 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology |
| spellingShingle | Harvard University--MIT Division of Health Sciences and Technology. Xiao, Xinshu Principal component based system identification and its application to the study of cardiovascular regulation |
| title | Principal component based system identification and its application to the study of cardiovascular regulation |
| title_full | Principal component based system identification and its application to the study of cardiovascular regulation |
| title_fullStr | Principal component based system identification and its application to the study of cardiovascular regulation |
| title_full_unstemmed | Principal component based system identification and its application to the study of cardiovascular regulation |
| title_short | Principal component based system identification and its application to the study of cardiovascular regulation |
| title_sort | principal component based system identification and its application to the study of cardiovascular regulation |
| topic | Harvard University--MIT Division of Health Sciences and Technology. |
| url | http://hdl.handle.net/1721.1/34202 |
| work_keys_str_mv | AT xiaoxinshu principalcomponentbasedsystemidentificationanditsapplicationtothestudyofcardiovascularregulation |