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Equine Distress Monitor

Recent studies from the American Horse Council (AHC) show that the horse industry in the United States contributes $39 billion in direct economic impact to the US economy and supports 1.4 million jobs on a full-time basis. However, a high horse fatality rate negatively impacts the overall industry performance. Colic was second only to old age as the major cause of equine death. The incidence of colic was 4.2 events per 100 horses per year, regardless of breed, use, or sex; and a case fatality rate of 11%. Death of horses with colic, the high average cost of care for horses that required surgery, and the number of horses that require surgery contributed to the cost of colic which the USDA estimated to be $115 million annually. Researchers at Utah State University have identified the need to reduce the frequency of these situations and have developed a novel sensor system for continuous monitoring of horses to detect and analyze behaviors that can indicate a variety of health conditions, such as colic or casting, which may result in serious injury to the animal.
   
Applications
Features and Benefits
  • Continuous autonomous animal health monitoring in stall, pens, and pastures
  • High-alert monitoring in breeding centers, show barns, and veterinary facilities
  • Health monitoring in trailers during transportation, when animals are at especially high risk

 

  • Timely detection and analysis of animal behavioral actions that indicate trauma, distress, or other serious conditions, increasing response time
  • Automated communication allowing immediate staff intervention, thus preventing permanent horse damage or death
  • Around-the-clock automated checks on horses, decreasing cost on extra supervising staff
  • Wireless communication method, allowing coverage of large facilities
    Managed power capability that provides long battery life and system reliability
 
Technology
The technology includes a wearable sensor system that records movements and correlates behavioral patterns with the health and safety of animals. Sensors mounted on the animal collect motion. If relevant motion is detected, the pattern recognition algorithms analyze the data to determine if the animal is in a distress situation or experiencing another type of behavior that requires intervention. The system correlates the analyzed motion data with characteristic animal behaviors and wirelessly transmits it to a base station. If distress is identified and intervention is required, the base-station automatically sends an alert to the staff.
 
Development Stage
A functioning prototype device has been successfully developed and tested. Opportunities are available to license the technology. 
 
Patent Pending
 
CONTACT INFORMATION
Glenn Whichard
Senior Commercialization Associate
Physical Sciences
Glenn.Whichard@usu.edu
(435) 797-9604
Reference: W08057
www.ipso.usu.edu

 

 

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