Monitoring system for animal husbandry

• US 20060155172A1
• Filed: 08/05/2005
• Published: 07/13/2006
• Est. Priority Date: 08/05/2004
• Status: Active Grant

• Current Assignee: Bio Equidae LLC
• Original Assignee: Bio Equidae LLC
• Inventors: Rugg, Geoffrey
• Granted Patent: US 7,335,168 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A01K 29/005 Monitoring or measuring activity, e.g. detecting heat or mating
• CPC Class Codes: A61B 2503/40 Animals
• CPC Class Codes: A61B 2560/045 with a separable interface unit, e.g. for communication
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/1113 Local tracking of patients, e.g. in a hospital or private home
• CPC Class Codes: A61B 5/112 Gait analysis
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/6814 Head
• CPC Class Codes: A61B 5/6829 Foot or ankle
• CPC Class Codes: A61D 17/00 Devices for indicating trouble during labour of animals ; Methods or instruments for detecting pregnancy-related states of animals monitoring or measuring activity of animals A01K29/005
• CPC Class Codes: G16H 40/60 for the operation of medical equipment or devices
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics

Abstract

A monitoring system (800) is operative for receiving sensor signals and analyzing the sensor signals to identify events or conditions of interest, such as colic, with respect to a monitored animal. The sensors may be animal-borne sensors such as motion related sensors. The system (800) includes a processor (802) operative to identify the conditions of interest based on a stored pattern database (806), threshold tables (808) and heuristic engines (812). Upon identification of a condition of interest, a human expert may be consulted and alerts may be generated as required.

Claims

1. A method for use in monitoring a horse to detect a colic related event, comprising the steps of:

providing at least one horse-borne sensor for generating a sensor signal potentially indicative of said colic related event;

operating said sensor to provide said sensor signal; and

outputting data based on said sensor signal to a processor operative for identifying said colic related event based at least in part on said sensor signal.

2. A method as set forth in claim 1, wherein said step of providing comprises attaching said sensor to said horse.

3. A method as set forth in claim 1, wherein said step of providing comprises attaching multiple sensors to said horse.

4. A method as set forth in claim 1, wherein said step of providing comprises providing a first sensor of a first type for sensing a first indication related to said colic related event and providing a second sensor of a second type, different than said first type, for sensing a second indication related to said colic related event.

5. A method as set forth in claim 1, wherein said step of providing comprises attaching said sensor to said horse proximate to a hoof of said horse.

6. A method as set forth in claim 5, wherein said step of attaching comprises adhesively bonding said sensor to said hoof of said horse.

7. A method as set forth in claim 1, wherein said step of providing comprises attaching said sensor to said horse proximate to a head of said horse.

8. A method as set forth in claim 1, wherein said step of operating comprises providing a substantial continuous output stream from said sensor signal.

9. A method as set forth in claim 1, wherein said step of operating comprises monitoring said horse at least overnight.

10. A method as set forth in claim 1, wherein said step of outputting comprises using a wireless connection to transmit said data between said sensor and said processor.

11. A method as set forth in claim 1, further comprising the step of operating said processor to identify said colic related event.

12. A method for use in monitoring a horse to detect a colic related event, comprising the steps of:

receiving a signal from at least one horse-borne sensor, wherein said signal is potentially indicative of said colic related event; and

analyzing said sensor signal to identify said colic related event.

13. A method as set forth in claim 12, wherein said step of receiving comprises obtaining information based on a wireless signal.

14. A method as set forth in claim 12, wherein said step of receiving comprises obtaining a digital signal transmitted via a WAN.

15. A method as set forth in claim 12, wherein said step of receiving comprises obtaining information from multiple horse-borne sensors.

16. A method as set forth in claim 15, wherein said multiple sensors are associated with multiple horses.

17. A method as set forth in claim 16, wherein said step of receiving comprises distinguishing portions of said information associated with different ones of said sensors.

18. A method as set forth in claim 12, wherein said step of analyzing comprises comparing said sensor signal to stored pattern information.

19. A method as set forth in claim 12, wherein said sensor provides motion related information and said step of analyzing comprises correlating said motion related information to defined animal behaviors.

20. A method as set forth in claim 12, wherein said step of analyzing comprises implementing a multi-variant analysis.

21. An apparatus for use in monitoring a horse to detect a colic related event, comprising:

at least one sensor, attached to said horse, for providing a sensor signal potentially indicative of said colic related event; and

interface structure for outputting said sensor signal to a processor operative for identifying said colic related event based at least in part on said sensor signal.

22. An apparatus as set forth in claim 21, further comprising an adhesive for use in attaching said sensor to said horse.

23. An apparatus as set forth in claim 21, wherein said at least one sensor comprises a first sensor and a second sensor.

24. An apparatus as set forth in claim 23, wherein said first sensor is of a first type for sensing a first indication related to said colic related event and said second sensor is of a second type, different than said first type, for sensing a second indication related to said colic related event.

25. An apparatus as set forth in claim 21, further comprising tack structure for use in attaching said sensor to said horse.

26. An apparatus as set forth in claim 21, wherein said interface structure comprises structure for at least one of transmitting and receiving a wireless signal.

27. An apparatus for use in monitoring a horse to detect a colic related event, comprising:

interface structure for receiving an input based on a sensor signal from a horse-borne sensor; and

a processor for analyzing said input to identify said colic related event.

28. An apparatus as set forth in claim 27, wherein said interface structure comprises structure for at least one of transmitting and receiving a wireless signal.

29. An apparatus as set forth in claim 27, wherein said interface structure comprises structure for receiving a digital signal via a wide area network.

30. An apparatus as set forth in claim 27, wherein processor is operative for comparing said input to store pattern information.

31. An apparatus as set forth in claim 27, wherein said input provides motion related information and said processor is operative for correlating said motion related information to defined animal behaviors.

32. An apparatus as set forth in claim 27, wherein said processor is operative for implementing a multi-variant analysis.