Method, device and system for cardio-acoustic signal analysis

• US 7,753,856 B2
• Filed: 04/14/2008
• Issued: 07/13/2010
• Est. Priority Date: 10/14/2005
• Status: Active Grant

• Current Assignee: Medicalgorithmics Ltd. (Medicalgorithmics S.A.)
• Original Assignee: Medicalgorithmics Ltd. (Medicalgorithmics S.A.)
• Inventors: Dziubinski, Marek
• Primary Examiner(s): Layno; Carl H
• Assistant Examiner(s): Stice; Paula J
• Application Number:
  US12/102,470
• Publication Number:
  US 20080260173A1
• Time in Patent Office: 820 Days
• Field of Search: 600/528, 600/480, 600/450, 600/463, 600/514, 128699-670
• US Class Current: 600/528
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A method for cardio-acoustic signal analysis includes receiving a signal representative of heart sounds and displaying the signal in a time-perceptual frequency-perceptual loudness domain representation. The received signal is transformed to represent a time-perceptual frequency-amplitude domain. The method further includes applying a human auditory modeling algorithm to the time-perceptual frequency-amplitude domain representation to generate the time-perceptual frequency-perceptual loudness domain representation.

Claims

1. A method for cardio-acoustic signal analysis, comprising:

receiving, via a signal receiver, a signal representative of heart sounds;

transforming, via a processing unit, the received signal to represent a time, perceptual-frequency, amplitude domain;

applying, via the processing unit, a human auditory system modeling algorithm to the time, perceptual frequency, amplitude domain representation to generate a time, perceptual-frequency, perceptual-loudness domain representation; and

displaying, via a visualization unit, the received signal in the time, perceptual-frequency, perceptual-loudness domain representation.

2. The method of claim 1, wherein the transformation is based on inner product calculations using a finite impulse response (FIR) filter bank representing a non-linear frequency resolution.

3. The method of claim 2, wherein the finite impulse response filter bank is complex numbered and represents properties of perceptual-frequency characteristics.

4. The method of claim 3, wherein the perceptual-frequency characteristics correspond to critical bands of hearing and represent a Bark frequency scale.

5. The method of claim 3, wherein the complex numbered impulse responses filter bank allow for calculating phase prediction and amplitude prediction of spectral components.

6. The method of claim 5, further comprising calculating, via the processing unit, tonality using an unpredictability measure parameter.

7. The method of claim 6, further comprising distinguishing, via the processing unit, between noisy and tonal components in the received signal.

8. The method of claim 7, further comprising simulating, via the processing unit, periodicity perception of the received signal.

9. The method of claim 1, further comprising interpreting, via the processing unit, the time, perceptual-frequency, perceptual-loudness domain representation for cardio-acoustic signal analysis.

10. The method of claim 9, wherein interpreting the time-perceptual frequency-perceptual loudness domain representation includes comparing, via the processing unit, the time, perceptual-frequency, perceptual-loudness domain representation to a perceived acoustical phenomena.

11. The method of claim 1, wherein the received signal is representative of at least cardiac auscultation and pulmonary auscultation.

12. The method of claim 1, further comprising applying, via the processing unit, periodicity analysis methods to the time, perceptual-frequency, perceptual-loudness domain representation.

13. The method of claim 12, further comprising detecting, via the processing unit, S1 and S2 of at least 2 cardiac cycles for calculating an averaged cardiac cycle representation.

14. The method of claim 13, further comprising limiting, via the processing unit, influence of noise and other non-repetitive parasite artifacts and disturbances to the received signal.

15. The method of claim 13, further comprising restoring, via the processing unit, the cardiac auscultation signal to remove noise, parasite clicks, or any combination thereof.

16. The method of claim 1, wherein the applying the human auditory system modeling algorithm simulates psychoacoustic masking phenomena.

17. A system for cardio-acoustic signal analysis, comprising:

an input sensor for receiving a signal representative of heart sounds;

a transformation module for transforming the receive signal to represent a time, perceptual-frequency, perceptual-loudness domain; and

a display device for displaying the received signal in the time, perceptual-frequency, perceptual-loudness domain.

18. A system for cardio-acoustic signal analysis, comprising:

means for receiving a signal representative of heart sounds;

means for transforming the received signal to represent a time, perceptual-frequency, perceptual-loudness domain; and

means for displaying the received signal in a time, perceptual-frequency, perceptual-loudness domain representation.