Flow Meter

• US 20150002668A1
• Filed: 09/19/2014
• Published: 01/01/2015
• Est. Priority Date: 12/21/2011
• Status: Active Grant

• Current Assignee: Deka Products Limited Partnership
• Original Assignee: Deka Products Limited Partnership
• Inventors: Peret, Bob D., Kane, Derek G.
• Granted Patent: US 9,724,466 B2
• Time in Patent Office: Days
• US Class Current: 348/143
• CPC Class Codes: A61M 1/3627 Degassing devices; Buffer reservoirs; Drip chambers; Blood filters
• CPC Class Codes: A61M 2205/3306 Optical measuring means
• CPC Class Codes: A61M 2205/3334 Measuring or controlling the flow rate
• CPC Class Codes: A61M 2205/50 with microprocessors or computers
• CPC Class Codes: A61M 39/284 Lever clamps
• CPC Class Codes: A61M 5/16886 for measuring fluid flow rate, i.e. flowmeters
• CPC Class Codes: A61M 5/1689 Drip counters
• CPC Class Codes: G01D 5/342 the sensed object being the obturating part
• CPC Class Codes: G01F 22/00 Methods or apparatus for measuring volume of fluids or fluent solid material, not otherwise provided for
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/20061 Hough transform
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 2207/20224 Image subtraction
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 7/248 involving reference images or patches
• CPC Class Codes: G06T 7/254 involving subtraction of images

Abstract

An flow meter includes a coupler, a support member, an image sensor, and one or more processors. The coupler is adapted to couple to a drip chamber. The support member is operatively coupled to the coupler. The image sensor has a field of view and is operatively coupled to the support member. The image sensor is positioned to view the drip chamber within its field of view. The one or more processors are operatively coupled to the image sensor to receive data thereform. The one or more processors (1) receive image data from the image sensor, and (2) determine an existence of a free flow condition by identifying an optical distortion of an area behind the free flow condition within the drip chamber using the received image data.

Claims

1. A flow meter, comprising:

a coupler adapted to couple to a drip chamber;

a support member operatively coupled to the coupler;

an image sensor having a field of view and operatively coupled to the support member, wherein the image sensor is positioned to view the drip chamber within the field of view;

a background pattern positioned within the field of view of the first image sensor wherein the drip chamber is between the image sensor and the background pattern, wherein the background pattern includes an array of lines having at least one angle relative to an opening of the drip chamber when viewed from the image sensor within the field of view; and

at least one processor operatively coupled to the image sensor, wherein the at least one processor is configured to;

receive image data from the image sensor, the image data including an image at least a portion of the background pattern,

compare the image data to a background image to generate a difference image, wherein the difference image corresponds to differences between the image data and the background image; and

determine whether a free flow condition exists in accordance with the difference image.

2. The flow meter according to claim 1, wherein the at least processor is configured to determine a free flow condition exists when the liquid causes the array of lines to change angles by distortion caused by the liquid when in the free flow condition as viewed within the field of view from the image sensor.

3. The flow meter according to claim 1, wherein the processor is configured to sum a plurality of summations along a direction of the difference image.

4. The flow meter according to claim 3, wherein the direction is parallel to each of a plurality of rows of the difference image.

5. The flow meter according to claim 1, wherein the processor is configured:

to sum each row of the difference image to calculate a plurality of row summations,

determine if a predetermined number of contiguous row summations of the plurality of row summations are above a threshold value, and

determine the free flow condition exists if the determined number of contiguous row summations of the plurality of row summations above the threshold value is greater than a threshold number of row summations.

6. The flow meter according to claim 1, wherein the processor is configured:

to sum each row of the difference image to calculate a plurality of row summations,

determine if a predetermined number of contiguous row summations of the plurality of row summations are above a threshold value, and

determine the free flow condition does not exist if the determined number of contiguous row summations of the plurality of row summations above the threshold value is not greater than a threshold number of row summations.

7. The flow meter according to claim 1, wherein the difference image is a difference between the image and the background image.

8. The flow meter according to claim 1, wherein the difference image is an absolute difference between the image and the background image.

9. The flow meter according to claim 1, wherein the difference image is a squared absolute difference between the image and the background image.

10. The flow meter according to claim 1, wherein the at least one processor is configured to determine that the free flow condition exists if a template matches the difference image.

11. A method, comprising:

capturing an image including an image of a drip chamber using an image sensor having a field of view including the drip chamber;

subtracting the image from a background image to thereby generate a difference image;

converting each pixel of the difference image to a true value if an absolute value of a respective pixel is greater than a predetermined threshold or to a false value if the absolute value of the respective pixel is less than the predetermined threshold;

summing each row of the converted difference image to generate a plurality of summation values, wherein each summation value of the plurality of summation values corresponds to a respective row of the converted difference image; and

examining the plurality of summation values.

12. The method according to claim 11, wherein the act of examining the plurality of summation values includes determining if a free flow condition exists within the drip chamber.

13. The method according to claim 12, wherein the act of determining if the free flow condition exists includes determining if the plurality of summation values includes a plurality of contiguous summation values above another predetermined threshold.

14. The method according to claim 11, wherein the act of examining the plurality of summation values includes determining if a drop has been formed within the drip chamber.

15. The method according to claim 14, wherein the act of determining if the drop has been formed within the drip chamber includes determining if the plurality of summation values includes a plurality of contiguous summation values within a predetermined range greater than a minimum value and less than a maximum value.

16. The method according to claim 11, further comprising smoothing the plurality of summation values prior to the examining act.

17. The method according to claim 16, wherein the smoothing act is in accordance with at least one of a spline function, a cubic spline function, a B-spline function, a Bezier spline function, a polynomial interpolation, a moving average, a data smoothing function, and a cubic-spline-type function.

18. The method according to claim 11, wherein the method is implemented by an operative set of processor executable instructions stored on a non-transitory processor-readable memory in operative communication with at least one processor such that the at least one processor performs the method.

19. The method according to claim 18, wherein:

the at least one processor is coupled to the image sensor, and

the at least one processor performs the method using the image sensor.

20. The method according to claim 11, further comprising converting each pixel of the difference image to an absolute value of each pixel after the subtracting act and prior to the converting act.

21. The method according to claim 11, further comprising converting each pixel of the difference image to a squared value of each pixel after the subtracting act and prior to the converting act.