Echocardiographic measurements as predictors of racing success

• US 8,061,302 B2
• Filed: 03/31/2009
• Issued: 11/22/2011
• Est. Priority Date: 07/17/2002
• Status: Expired due to Fees

• Current Assignee: Equine Biomechanics and Exercise Physiology Incorporated
• Original Assignee: Equine Biomechanics and Exercise Physiology Incorporated
• Inventors: Seder, Jeffrey A.
• Primary Examiner(s): PARSLEY, DAVID J
• Application Number:
  US12/414,962
• Publication Number:
  US 20090192975A1
• Time in Patent Office: 966 Days
• Field of Search: 119/174
• US Class Current: 119/174
• CPC Class Codes: A61B 8/0858 involving measuring tissue layers, e.g. skin, interfaces
• CPC Class Codes: A61B 8/463 characterised by displaying multiple images or images and diagnostic data on one display composite display in devices for short-range imaging with acoustic waves G01S7/52074
• CPC Class Codes: A63K 3/00 Equipment or accessories for racing or riding sports training equipment for animals A01K15/02
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 99/00 Subject matter not provided for in other groups of this subclass

Abstract

The present invention is directed to methods for selecting racehorse candidates. Provided herein are methods for increasing the likelihood of selecting candidates that will be high earners, while reducing the likelihood of selecting candidates that will be low earners, on the basis of certain ultrasonographically-obtained cardiac measurements.

Claims

1. A non-transitory computer-readable storage medium for selecting a racehorse candidate having a better than average likelihood of becoming a high earner, the computer-readable storage medium having stored therein computer executable instructions that when executed by a processor cause the processor to perform the steps comprising:

(i) receiving first data indicative of an ultrasonographically-obtained measurement of the width of the ventricular septal wall of an unraced racehorse candidate;

(ii) retrieving a stored data set comprising ultrasonographically-obtained measurements from a group of horses, wherein said collection of measurements comprises ventricular septal wall width measurements for at least about 75 horses of about the same age, sex, and weight as said racehorse candidate; and

(iii) generating a prediction indication from a comparison of the first data and the data set, wherein the comparison determines whether the unraced racehorse candidate has an ultrasonographically-obtained ventricular septal wall width measurement that is greater than the mean ultrasonographically-obtained ventricular septal wall width measurement from said data set, said determination based on a comparison of said first data with said data set; and

(iv) outputting the prediction indication.

2. The non-transitory computer-readable medium of claim 1, wherein said comparison of the first data and the data set determines whether said unraced racehorse candidate has a ventricular septal wall width that is in the 75th percentile or higher as compared to the ventricular septal wall width measurements from said data set.

3. A computer system for selecting an unraced racehorse candidate having a better than average likelihood of becoming a high earner, the computer system comprising:

a memory having stored therein a data set comprising ultrasonographically-obtained measurements from a group of horses, wherein said collection of measurements comprises ventricular septal wall width measurements for at least about 75 horses of about the same age, sex, and weight as said racehorse candidate; and

a processor that (i) receives first data indicative of an ultrasonographically-obtained measurement of the width of the ventricular septal wall of said racehorse candidate, (ii) retrieves the data set from the memory, (iii) generates a prediction indication from a comparison of the first data and the data set, wherein the comparison determines whether the racehorse candidate has an ultrasonographically-obtained ventricular septal wall width measurement that is greater than the mean ultrasonographically-obtained ventricular septal wall width measurement from said data set, and (iv) outputs the prediction indication.

4. The computer system of claim 3, wherein said comparison of the first data and the data set determines whether said racehorse candidate has a ventricular septal wall width that is in the 75th percentile or higher as compared to the ventricular septal wall width measurements from said data set.

5. An racehorse candidate selection computer system for selecting a racehorse candidate having a better than average likelihood of becoming a high earner comprising:

an ultrasound imaging machine with electronic calipers to generate first data indicative of a measurement of the width of the ventricular septal wall of an unraced racehorse candidate;

a memory having stored therein a data set comprising ultrasonographically-obtained measurements from a group of horses, wherein said collection of measurements comprises ventricular septal wall width measurements for at least about 75 horses of about the same age, sex, and weight as said racehorse candidate; and

a processor that (i) receives first data indicative of an ultrasonographically-obtained measurement of the width of the ventricular septal wall of said unraced racehorse candidate, (ii) retrieves the data set from the memory, (iii) generates a prediction indication from a comparison of the first data and the data set, wherein the comparison determines whether the unraced racehorse candidate has an ultrasonographically-obtained ventricular septal wall width measurement that is greater than the mean ultrasonographically-obtained ventricular septal wall width measurement from said data set, and (iv) outputs the prediction indication.

6. The system of claim 5, wherein said comparison of the first data and the data set determines whether said unraced racehorse candidate has a ventricular septal wall width that is in the 75th percentile or higher as compared to the ventricular septal wall width measurements from said data set.