1 / 19

The Energy Operator: A Useful Diagnostic Tool

The Energy Operator: A Useful Diagnostic Tool. Balu Santhanam SPCOM Lab, Dept. of E.E.C.E. University of New Mexico Email: bsanthan@eece.unm.edu. Overview of Talk. Energy Operator Primer. Biomedical Applications. Diagnostic Applications. ECG Example. Teager-Kaiser Energy Operator.

cece
Download Presentation

The Energy Operator: A Useful Diagnostic Tool

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The Energy Operator: A Useful Diagnostic Tool Balu Santhanam SPCOM Lab, Dept. of E.E.C.E. University of New Mexico Email: bsanthan@eece.unm.edu

  2. Overview of Talk • Energy Operator Primer • Biomedical Applications • Diagnostic Applications • ECG Example

  3. Teager-Kaiser Energy Operator • Continuous signals • Discrete Signals

  4. Higher-order Energy Operators Continuous Signals: Discrete Signals:

  5. Energy Separation Algorithm • Monocomponent AM-FM Signals: • Instantaneous Frequency (IF) and Amplitude (IA)

  6. Multi-band Demodulation • Filter signal via a bandpass filter-bank with optimized center-frequency and bandwidth. • Pick the most active branch based on the energy-operator output. • Demodulate output of selected branch using the ESA into IA/IF signals.

  7. Features of E - Operators (1) • The energy operator output for sinusoidal sources produces the normalized energy. • For slowly time-varying sources, the energy operator tracks the energy of the source. • Instantaneous behavior allows tracking of abrupt changes in energy.

  8. Features of E - Operators (2) • Higher-order energy operators track higher-order energies of a signal source. • For k = 2 : HOEO  TKEO. • Energy operators possess simplicity, efficiency and good time-resolution.

  9. Biomedical Applications • Used to detect vocal-tract defects and pathologies • Used to detect spikes in neural (EEG) output • Used for EEG segmentation and abrupt event detection. • Used for detection of heart murmurs, sleep apnea disorder, heart rate variability measurements.

  10. Vocal Tract Pathologies • Improper glottal closure: whisper phonation, creaky voice, glottal blow, etc. • Pathologies: polyps, papillomas, carcinoma, contact ulcers, nerve paralysis. • Vocal tract asymmetry produces two different fundamental frequencies • IA/IF estimates facilitate detection of normal/pathological cases.

  11. EEG Applications • EEG provides a sensitive indicator of cerebral function. • Spikes in the EEG output characterize epileptic seizures. • IA and IF information from segmented EEG serve as a useful diagnostic tools.

  12. Cardio Applications (1) • ECG signal exhibits quasi-periodicity producing regular peaks (R-waves) • Respiratory sinus arythmia (RSA) constitutes frequency modulation in the ECG signal. • The heart-IF (HIF) can be used to estimate heart-rate variability.

  13. Cardio Applications (2) • Instantaneous energy and IF can be used to classify heart sound and murmurs. • IA and IF of cardiac inter-beat times can be used to detect obstructive sleep-apnea (OSA). • Two component chirp model used to model pulmonary and aortic components of second heart sound (dub)

  14. ECG Example – 1

  15. ECG Example - 2

  16. ECG Example - 3

  17. ECGExample – 4

  18. References – 1 [BaOh01]: A. Barros and N. Ohnishi, “Heart Instantaneous Frequency (HIF): An alternative Approach to Extract Heart Rate Variability,” IEEE Trans. On Biomed. Engg., Aug, 2001. [Miet00]: J.E. Mietus et.al., “Detection of Obstructive Sleep Apnea from Cardiac Interbeat Interval Time Series,” Computers in Cardiology, 2000. [Shar00]: Sharif et. al., “Analysis and Classification of Heart Sounds and Murmurs Based on the Instantaneous Energy and Frequency Estimations,” Proceedings of TENCON, 2000. [MuRa98]: S. Mukhopadhyay and G.C. Ray, “A New Interpretation of Nonlinear Energy Operator and Its Efficacy in Spike Detection,” IEEE Trans. On Biomed. Engg. Feb. 2000.

  19. References - 2 • [XDP01]: J. Xu, L-G. Durand and P. Pibarot, “Nonlinear Transient Chirp Signal Modeling of the Aortic and Pulmonary Components of the Second Heart Sound,” IEEE Trans. On Biomed. Engg., March 2001. • [XDP00] : J. Xu, L-G. Durand and P. Pibarot, “Extraction of the Aortic and Pulmonary Components of the Second Heat Sound Using a Nonlinear Transient Chirp Signal Model,” IEEE Trans. On Biomed. Engg., July 2000. • [AgGo99]: R. Agarwal and J. Gotman, “Adaptive Segmentation of EEG Data Using A Nonlinear Energy Operator,” 1999. • [HCK98] : J.H.L. Hansen, L.G.-Ceballos, and J.F. Kaiser, “A Nonlinear Operator-Based Speech Feature Analysis Method with Application to Vocal Fold Pathology Assessment,” IEEE Trans. On Biomed. Engg., March 98

More Related