Fat depth sensor

• US 7,089,047 B2
• Filed: 06/13/2002
• Issued: 08/08/2006
• Est. Priority Date: 12/13/1999
• Status: Expired due to Fees

• Current Assignee: Callaghan Innovation
• Original Assignee: Industrial Research Limited
• Inventors: Holmes, Wayne Stephen
• Primary Examiner(s): Smith, Ruth S.
• Application Number:
  US10/173,226
• Publication Number:
  US 20030013954A1
• Time in Patent Office: 1,517 Days
• Field of Search: 600/407, 600/430, 128/920
• US Class Current: 600/430
• CPC Class Codes: A22B 5/007 Non-invasive scanning of carcasses, e.g. using image recognition, tomography, X-rays, ultrasound analysing meat, e.g. search for foreign embedded objects G01N33/12; image analysis G06T7/00
• CPC Class Codes: A61B 2503/40 Animals
• CPC Class Codes: A61B 5/0507 using microwaves or terahertz waves
• CPC Class Codes: A61B 5/4872 Body fat
• CPC Class Codes: G01B 15/02 for measuring thickness
• CPC Class Codes: G01N 22/00 Investigating or analysing materials by the use of microwaves or radio waves, i.e. electromagnetic waves with a wavelength of one millimetre or more G01N3/00 - G01N17/00, G01N24/00 take precedence
• CPC Class Codes: G01N 33/12 Meat; Fish
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics

Abstract

A non-invasive sensor suitable for measuring the depth of fat in animal tissue is described, the sensor generating and transmitting focussed discrete narrow band microwave signals into the tissue, receiving reflected microwave signals from the tissue and providing magnitude and phase information of the reflected microwave signals for a processor to compute a value of the fat depth within the tissue.

Claims

1. A non-invasive sensor suitable for measuring the depth of fat in tissue, the sensor including:

microwave signal generation and transmission means adapted to generate and transmit microwave signals into the tissue;

focussing means adapted to focus the microwave signals onto a predetermined focal point;

control means adapted to control the microwave signal generation and transmission means to transmit, in use, at least three discrete narrow band microwave signals into the tissue;

receiving means adapted to receive reflected microwave signals from the tissue and provide magnitude and phase information of the reflected microwave signals; and

processing means for receiving the magnitude and phase information provided by the receiving means and computing a value suitable for identification of the fat depth within the tissue.

2. A non-invasive sensor as claimed in claim 1, wherein the microwave generation and transmission means generates and transmits microwave signals in the X-band.

3. A non-invasive sensor as claimed in claim 1, wherein the receiving means includes a six port reflectometer.

4. A non-invasive sensor as claimed in claim 1, wherein the focussing means includes a lens system.

5. A non-invasive sensor as claimed in claim 1, wherein the processing means is programmed to compute the reflection coefficient of received microwave signals.

6. A non-invasive sensor as claimed in claim 5, wherein the processing means is programmed to compute the phase of the received microwave signals from the reflection coefficient.

7. A non-invasive sensor as claimed in claim 1 wherein the processing means is programmed to compute the depth of fat by first computing the electrical length of the fat and computing the permittivity of the tissue at the focal point, and computing the depth of fat from the electrical length divided by the square root of the permittivity.

8. A non-invasive sensor as claimed in claim 7, wherein the processing means is programmed to compute the electrical length (d_e) of the fat and permittivity (ε

_r) of the tissue by computing the values of electrical length and permittivity that minimise the error function

$\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br><br><br>\left[{\tan }^2<br><br>\frac{{\mathrm{\theta <br><br>}}_i}{2}-\frac{1}{{\mathrm{\varepsilon <br><br>}}_r}<br><br>{\tan }^2<br><br>\left[\frac{2<br><br>\mathrm{\pi <br><br>}<br><br><br><br>f_1·<br><br>d_e}{c}\right]\right]=0$

or is programmed to perform an equivalent computation, wherein θ

_i is the phase of the received microwave signals, f₁ is the frequency of the received signals or frequency of the transmitted signal, c is speed of the microwave signals and N is the number of discrete narrow band signals transmitted into the tissue for the purposes of the measurement.

9. A non-invasive sensor as claimed in claim 8, wherein the processing means is programmed to compute the reflection coefficient of reflected microwave signals from the magnitude information from the receiving means and compute the phase of the received microwave signals from the reflection coefficient.

10. A non-invasive sensor as claimed in claim 8, wherein the processing means is programmed to use at least one iterative regression analysis technique to minimise the error function.

11. A non-invasive sensor as claimed in claim 1, wherein, the sensor includes a positioning means adapted to position the focal point of the focussing means on an outer boundary of a fat layer.

12. A non-invasive sensor as claimed in claim 11, wherein the position determination means is a laser sensor or a tactile sensor.

13. A non-invasive sensor as claimed in claim 1, wherein, the sensor includes a means for orienting the sensor so that the microwave signals are transmitted through an outer surface of the fat substantially transverse to the outer surface of the fat.

14. A method of sensing the depth of fat in tissue including:

generating and transmitting three or more focussed discrete narrow band microwave signals into the tissue;

sensing the magnitude and phase of reflected microwave signals from the tissue;

computing from the sensed magnitude and phase a value suitable for identification of the fat depth within the tissue.

15. The method of claim 14, wherein the method further includes the step of generating and transmitting microwave signals in the X-band.

16. The method of claim 14 including sensing the magnitude and phase of the reflected microwave signals using a six port reflectometer.

17. The method of claim 14 including focussing the microwave signals using a lens system.

18. The method of claim 14, wherein the method further includes the step of computing the depth of fat by first computing the electrical length of the fat and computing the permittivity of the tissue at the focal point, and computing the depth of fat from the electrical length divided by the square root of the permittivity.

19. The method of claim 18, wherein the method further includes the step of computing the electrical length (d_e) of the fat and permittivity (ε

_r) of the tissue by minimising the error function

$\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br><br><br>\left[{\tan }^2<br><br>\frac{{\mathrm{\theta <br><br>}}_i}{2}-\frac{1}{{\mathrm{\varepsilon <br><br>}}_r}<br><br>{\tan }^2<br><br>\left[\frac{2<br><br>\mathrm{\pi <br><br>}<br><br><br><br>f_1·<br><br>d_e}{c}\right]\right]=0$

or an equivalent, wherein θ

_i is the phase of the received microwave signals, f₁ is the frequency of the received signals or frequency of the transmitted signal, c is speed of the microwave signals and N is the number of discrete narrow band signals transmitted into the tissue for the purposes of the measurement.

20. The method of claim 19, wherein the method further includes the step of computing the reflection coefficient of reflected microwave signals from the sensed magnitude and computing the phase of the received microwave signals from the reflection coefficient.

21. The method of claim 19, further including using at least one iterative regression analysis technique to minimise the error function.

22. The method of claim 14, wherein the step of transmitting three or more focussed discrete narrow band microwaves signals into the tissue includes focussing the narrow band microwave signals on to a focal point positioned on an outer surface of the fat.