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Snoring / Sleep Apnea Sound Analysis

Snoring / Sleep Apnea Sound Analysis . Jacob Zurasky ECE5525 Fall 2010. Snoring / Sleep Apnea Analysis. Goals Determine if the principles of speech processing relate to snoring sounds. Use homomorphic filtering techniques to analyze snoring for pitch and also vocal tract response.

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Snoring / Sleep Apnea Sound Analysis

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  1. Snoring / Sleep Apnea Sound Analysis Jacob Zurasky ECE5525 Fall 2010

  2. Snoring / Sleep Apnea Analysis • Goals • Determine if the principles of speech processing relate to snoring sounds. • Use homomorphic filtering techniques to analyze snoring for pitch and also vocal tract response. • Develop a method to distinguish a simple snore from a sleep apnea event.

  3. Background

  4. Past Research - SRD • Store amplitude and frequency spectrum data to SD card • Interface to Sleep Lab polysomnogram equipment

  5. SRD – Sample Data Output • Top Figure is the frequency spectrum (0-2kHz) • Bottom figure is the snore amplitude

  6. Past Research – iPhone App

  7. Homomorphic Filtering – Speech • Assume: s[n] = h[n] * p[n] • FFT -> log( ) -> IFFT, yields the cepstrum • Separate by low quefrencyliftering • FFT -> exp( ) -> IFFT, vocal tract response

  8. Homomorphic Filtering - Snoring • Assume: s[n] = h[n] * p[n] (palatal flow) • Use sliding hamming window, 50% overlap • Analyze different sounds clips for differences in h[n] and p[n] between normal snoring and an apnea event.

  9. Signal - apnea1.wav

  10. FFT – apnea1.wav

  11. Cepstrum – apnea1.wav

  12. Vocal Tract Response – apnea1

  13. Signal - apnea2.wav

  14. FFT – apnea2.wav

  15. Cepstrum – apnea2.wav

  16. Vocal Tract Response – apnea2

  17. Signal - snore1.wav

  18. FFT – snore1.wav

  19. Cepstrum – snore1.wav

  20. Vocal Tract Response – snore1

  21. Signal - snore2.wav

  22. FFT – snore2.wav

  23. Cepstrum – snore2.wav

  24. Vocal Tract Response – snore2

  25. Observations • p[n], ‘Voicing’, of the sleep apnea files has a much larger magnitude in the cepstral domain. • Vocal tract response during a simple snore is more stable than during an apnea. • Vocal tract response is slower changing during a simple snore.

  26. Future Goals • Redesign the SRD to incorporate the functions of the MATLAB code. • Faster processor, floating point architecture • Continue research to develop a method for in home screening of sleep apnea.

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