Recognition and localisation of pathologic animal and human sounds

• US 20090312660A1
• Filed: 06/17/2008
• Published: 12/17/2009
• Est. Priority Date: 06/17/2008
• Status: Abandoned Application

• Current Assignee: BioRICS NV, KU Leuven Research & Development
• Original Assignee: BioRICS NV, KU Leuven Research & Development
• Inventors: Guarino, Marcella, Silva, Mitchell, Exadaktylos, Vasileios, Ferrari, Sara, Costa, Annamaria, Borgonovo, Federica, Leroy, Toon, Aerts, Jean-Marie, Berckmans, Daniel
• Application Number:
  US12/213,254
• Publication Number:
  US 20090312660A1
• Time in Patent Office: Days
• US Class Current: 600/529
• CPC Class Codes: A61B 2503/40 Animals
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0823 Detecting or evaluating cough events
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• 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: A61B 7/003 Detecting lung or respiration noise
• CPC Class Codes: A61B 7/04 Electric stethoscopes microphones, acoustic transducers therefor H04R
• CPC Class Codes: G06F 2218/22 Source localisation; Inverse modelling
• CPC Class Codes: G10L 17/26 Recognition of special voice characteristics, e.g. for use in lie detectors; Recognition of animal voices
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/80 for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A system and method are described for combining the respiratory status (e.g. amount and type of cough) with the localization of organisms having the respiratory status in real time. The organisms are able to suffer from a respiratory complaint, i.e. they have lungs such as mammals especially farm animals and humans. In particular the present invention is advantageous for animals and humans who are exposed to closed confinements such as pens, cages, aircraft, public places where humans are in close proximity to each other.

Claims

1. A computer based method for monitoring a mammal, comprising:

capturing a remote cough event using one or more sensors,

analyzing the cough event to determine if it is indicative of a sick or healthy cough, and

localizing the cough event.

2. The method of claim 1, wherein the one or more sensors are one or more microphones

3. The method of claim 1, wherein the analyzing is done in real time.

4. The method of claim 1 wherein the analyzing includes any of Hidden Markov models or Dynamic Time warping, LPC, ARX-models or input-output models.

5. The method of claim 1, wherein the analyzing includes a first model that calculates characteristic parameter of the respiratory status from sound captured by the one or more microphones.

6. The method of claim 5, wherein the characteristic parameter is one of spectral content, an autoregressive model parameter or acoustic energy.

7. The method of claim 5, wherein the analyzing includes a second model to quantify the dynamic variation of the characteristic parameter.

8. The method of claim 7, further comprising classification of the cough event based on dynamic variation of the characteristic parameter.

9. The method of claim 1 further comprising extraction of sound information from the sound signal captured by the one or more sensors, by:

Calculating the energy of the sound signal,

Calculating the Hilbert transform of the energy,

Calculating the square root of the sum of the energy and its Hilbert transform,

Calculating the moving average of the result to get a smoothed estimate of the envelope of the initial signal.

10. The method of claim 1 wherein localizing the cough event comprises:

estimation of a time difference of arrival of the sound signal captured by the one or more microphones.

11. The method of claim 1, wherein localizing the cough event comprises any of:

energy thresholding, and

detecting simultaneous movements of the mammal.

12. The method of claim 11, wherein detecting simultaneous movements of the mammal is carried out by means of analysing images from a camera or by comparing the sound signal captured by the one or more microphones with an output of a movement detector.

13. The method of claim 12, wherein the movement detector is an accelerometer.

14. A computer based system for the recognition of respiratory status of a mammal, comprising:

one or more sensors for capturing a remote cough event,

means for analyzing the cough event to determine if it is indicative of a sick or healthy cough, with in both cases the possibility to classify it as a stress sick cough or a normal cough and

Means for localizing the cough event.

15. The system of claim 14, wherein the means for analyzing is adapted for real time operation.

16. The system of claim 14, wherein the means for analyzing is adapted to use Hidden Markov models or Dynamic Time warping, LPC, ARX models or input-output models.

17. The system of claim 14, wherein the means for analyzing is adapted to use a first model that calculates characteristic parameter of the respiratory status from sound captured by the one or more microphones.

18. The system of claim 17, wherein the characteristic parameter is one of spectral content, an autoregressive model parameter or acoustic energy.

19. The system of claim 17, wherein the means for analyzing is adapted to use a second model to quantify the dynamic variation of the characteristic parameter.

20. The system of claim 19, further comprising means for classification of the cough event based on dynamic variation of the characteristic parameter.

21. The system of claim 14 further comprising means for extraction of sound information from the sound signal captured by the one or more microphones, the means for extracting having:

means for calculating the energy of the sound signal,

means for calculating the Hilbert transform of the energy,

means for calculating the square root of the sum of the energy and its Hilbert transform, and

means for calculating the moving average of the result to get a smoothed estimate of the envelope of the initial signal.

22. The system of claim 14 wherein the means for localizing the cough event comprises:

means for estimation of a time difference of arrival of the sound signal captured by the one or more microphones.

23. The system of claim 14, wherein the means for localizing the cough event comprises any of:

means for energy thresholding, and

means for detecting simultaneous movements of the mammal.

24. The system of claim 23, wherein the means for detecting simultaneous movements of the mammal has means for analysing images from a camera or means for comparing the sound signal captured by the one or more microphones with an output of a movement detector.

25. The system of claim 24, wherein the movement detector is an accelerometer.

26. The system of claim 14 in which relevant information can be combined with environmental data selected from temperature, dust, pollutants and humidity.

27. A portable electronic device having a processing engine and a memory, comprising:

one or more microphones for capturing a remote cough event,

means for analyzing the cough event to determine if it is indicative of a sick or healthy cough, and

Means for localizing the cough event.