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Development of a foaling alarm system using an accelerometer

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초록

Horse breeders suffer massive economic losses due to dystocia, abortion, and stillbirths. In Thoroughbred mares, breeders often miss the foaling process because approximately 86% of the foaling events occur from 19:00 to 7:00; consequently, breeders cannot assist mares experiencing dystocia. To solve this problem, various foaling alarm systems have been developed. However, there is a need to develop a new system to overcome the shortcomings of the existing devices and improve their accuracy. To this end, the present study aimed to (1) develop a novel foaling alarm system and (2) compare its accuracy with that of the existing Foalert™ system. Specifically, eighteen Thoroughbred mares (11.9 ± 4.0 years old) were included. An accelerometer was used to analyze specific foaling behaviors. Behavioral data were transmitted to a data server every second. Depending on the acceleration value, behaviors were automatically classified by the server as categorized behaviors 1 (behaviors without change in body rotation), 2 (behaviors with sudden change in body rotation, such as rolling over), and 3 (behaviors with long-term change in body rotation, such as lying down laterally). The system was designed to alarm when the duration of categorized behaviors 2 and 3 was 12.9% and that of categorized behavior 3 was 1% during 10 min. The system measured the duration of each categorized behavior every 10 min and transmitted an alarm to the breeders when foaling was detected. To confirm its accuracy, the foaling detection time of the novel system was compared with that of Foalert™. The novel foaling alarm system and Foalert™ alarmed foaling onset respectively 32.6 ± 17.9 and 8.6 ± 1.0 min prior to foal discharge, and the foaling detection rate of both systems was 94.4%. Therefore, the novel foaling alarm system equipped with an accelerometer can precisely detect and alert foaling onset.

Abstract

Horse breeders suffer massive economic losses due to dystocia, abortion, and stillbirths. In Thoroughbred mares, breeders often miss the foaling process because approximately 86% of the foaling events occur from 19:00 to 7:00; consequently, breeders cannot assist mares experiencing dystocia. To solve this problem, various foaling alarm systems have been developed. However, there is a need to develop a new system to overcome the shortcomings of the existing devices and improve their accuracy. To this end, the present study aimed to (1) develop a novel foaling alarm system and (2) compare its accuracy with that of the existing Foalert™ system. Specifically, eighteen Thoroughbred mares (11.9 ± 4.0 years old) were included. An accelerometer was used to analyze specific foaling behaviors. Behavioral data were transmitted to a data server every second. Depending on the acceleration value, behaviors were automatically classified by the server as categorized behaviors 1 (behaviors without change in body rotation), 2 (behaviors with sudden change in body rotation, such as rolling over), and 3 (behaviors with long-term change in body rotation, such as lying down laterally). The system was designed to alarm when the duration of categorized behaviors 2 and 3 was 12.9% and that of categorized behavior 3 was 1% during 10 min. The system measured the duration of each categorized behavior every 10 min and transmitted an alarm to the breeders when foaling was detected. To confirm its accuracy, the foaling detection time of the novel system was compared with that of Foalert™. The novel foaling alarm system and Foalert™ alarmed foaling onset respectively 32.6 ± 17.9 and 8.6 ± 1.0 min prior to foal discharge, and the foaling detection rate of both systems was 94.4%. Therefore, the novel foaling alarm system equipped with an accelerometer can precisely detect and alert foaling onset.

참고문헌 (7)

  1. Rossdale PD, "The time of foaling of thoroughbred mares", J Reprod Fertil, 13, pp.341~343 (1967)[DOI]
  2. Shaw EB, "Body temperature and behaviour of mares during the last two weeks of pregnancy", Equine Vet J, 20, pp.199~202 (1988)[DOI]
  3. 정영욱, "Classification of behavioral signs of the mares for prediction of the pre-foaling period", 한국동물생명공학회지, 36(2), pp.99~105 (2021), 사단법인 한국동물생명공학회[DOI]
  4. Auclair-Ronzaud J, "No-contact microchip measurements of body temperature and behavioural changes prior to foaling", Theriogenology, 157, pp.399~406 (2020)[DOI]
  5. De Waele T, "Internet of animals : unsupervised foaling detection based on accelerometer data", 2021 IEEE 7th World Forum on Internet of Things (WF-IoT) (2021)
  6. Hartmann C, "Detection of the time of foaling by accelerometer technique in horses(Equus caballus)—a pilot study", Reprod Domest Anim, 53, pp.1279~1286 (2018)[DOI]
  7. Taylor PM, "Diagnosing and treating pain in the horse : where are we today?", Vet Clin North Am Equine Pract, 18, pp.1~19 (2002)[DOI]

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