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Ch 04 Event Detection

Ch 04 Event Detection. Epoch in biomedical signal. Physiological events. QRS complex. 0.1 mV. P  R segment. 0.04 ms. Q. S  T interval. S. P  R interval. Q  T interval. R. S  T segment. T. P. U. 4.2.1 ECG. 4.2.2 PCG. 4.2.3 Dicrotic notch. Carotid pulse

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Ch 04 Event Detection

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  1. Ch 04 Event Detection

  2. Epoch in biomedical signal Physiological events

  3. QRS complex 0.1 mV PR segment 0.04 ms Q ST interval S PR interval QT interval R ST segment T P U 4.2.1 ECG

  4. 4.2.2 PCG

  5. 4.2.3 Dicrotic notch Carotid pulse ** a pressure signal ** recorded over the carotid artery ** indicates the variations in arterial blood pressure and volume with each heart beat ** resembles the morphology of the pressure signal at the root of the aorta ** cannot be used to measure absolute pressure ** can assist in identifying S2 and its components

  6. Fig. 1-24 P (pressure wave)  blood ejection from LV T (tidal wave)  a reflected pulse returning from the upper body D (dicrotic notch)  closure of the aortic valve DW (dicrotic wave)  a reflected pulse from the lower body

  7. 4.2.4 EEG • The K-complex • (b) The lambda wave • (c ) the mu rhythm • (d) a spike • (e) sharp waves • (f) spike-and-wave complexes • (g) A sleep spindle • (h) Vertex sharp waves (V) • (i) Polyspike discharges

  8. 4.3 Detection of Events and Waves

  9. 4.3.1 Derivative-based methods for QRS detection Solution 1: Q: Why not search ECG for the QRS peak directly? A: QRS complex may not be the highest wave.

  10. 1 0.5 ECG, resample 0 -0.5 -1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 1 0.8 0.6 y0 0.4 0.2 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

  11. Solution 2:

  12. n-8 n-7 n-6 n-5 n-4 n-3 n-2 n-1 n

  13. 4.3.2 The Pan-Tompkins algorithm for QRS detection

  14. 4.3.3 Detection of the dicrotic notch

  15. 4.4 Correlation analysis of EEG channels

  16. 4.4.1 Detection of EEG rhythms

  17. Th EEG signals

  18. EEG p4 (Figure 4.8)

  19. EEG f3 (Figure 4.9)

  20. EEG p3 p4 (Figure 4.10)

  21. EEG o2 c4 (Figure 4.11)

  22. EEG f3 f4 (Figure 4.12)

  23. 4.4.2 Template matching for EEG spike-and wave detection

  24. Matched filter 4.4.2 Template matching for EEG spike-and wave detection

  25. Matched filter

  26. 4.5 Cross-spectral Techniques

  27. 4.5.1 Coherence analysis of EEG channels

  28. 4.6 The Matched Filter Usefulness: to detect signals of known characteristics that are buried in noise Operation: a correlation between the input signal and the template

  29. 4.6.1 Detection of EEG spike-and-wave complex

  30. Matched filter

  31. Impulse response

  32. 4.7 Detection of the P wave

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