Aysin, Benhur
(2002)
Orthonormal-Basis Partitioning And Time-Frequency Representation of Non-Stationary Signals.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Spectral analysis is important in many fields, such as speech, radar and biomedicine. Many signals encountered in these areas possess time-varying spectral characteristics. The power spectrum indicates what frequencies exist in the signal but it does not show when those frequencies occur. Time-frequency analysisprovides this missing information. A time-frequency representation of the signal shows the intensities of the frequencies in the signal at the times they occur, and thus reveals if and how the frequencies of a signal are changing over time.Time-dependent spectral analysis of beat-to-beat variations of cardiac rhythm, or heart rate variability (HRV), represents a major challenge due to the structure of the signal. A number oftime-frequency representations have been proposed for the estimation of the time-dependent spectra. However, time-frequency analysis of multicomponent physiological signals such as cardiac rhythm is complicated by the presence of numerous, ill-structured frequency elements. We sought to develop a simple method for 1)detecting changes in the structure of the HRV signal, 2)segmenting the signal into pseudo-stationary portions, and 3)exposing characteristic patterns of the changes in thetime-frequency plane. The method, referred to as Orthonormal-Basis Partitioning and Time-Frequency Representation (OPTR), is validated on simulated signals and HRV data. Unlike the traditional time-frequency HRV representations, which are usuallyapplied to short segments of signals recorded in controlled conditions, OPTR can be applied to long and "content-rich" ambulatory signals to obtain the signal representation along withits time-varying spectrum. Thus, the proposed approach extends the scope of applications of the time-frequency analysis to all types of HRV signals and to other physiological data.
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Details
| Item Type: |
University of Pittsburgh ETD
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| Status: |
Unpublished |
| Creators/Authors: |
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| ETD Committee: |
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| Date: |
20 December 2002 |
| Date Type: |
Completion |
| Defense Date: |
26 November 2002 |
| Approval Date: |
20 December 2002 |
| Submission Date: |
2 December 2002 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Electrical Engineering |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
eigenvector; feature extraction; spectral analysis; tilt |
| Other ID: |
http://etd.library.pitt.edu:80/ETD/available/etd-12022002-131851/, etd-12022002-131851 |
| Date Deposited: |
10 Nov 2011 20:07 |
| Last Modified: |
15 Nov 2016 13:52 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/9938 |
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