Lameness detection in sheep through behavioural sensor data analysis

Zainab Al-Rubaye

Research output: Contribution to conference typesPosterResearch

Abstract

Lameness is a clinical symptom referring to locomotion changes, resulting in impaired and erratic movements that differ widely from normal gait or posture. Lameness has an adverse impact on both sheep welfare and farm economy, therefore the preclinical detection of lameness will improve both sheep health and, in turn, support farming businesses. A newly developed sensor technology should enable automatic monitoring of animals to determine physiological and behavioural indicators, which would then be subsequently used as inputs into data analysis algorithms. The sensor that will be used to conduct this research is immensely accurate and sensitive. It provides acceleration, angular velocity, orientation, longitude, latitude and the time of reading which can be set up according to the demanded accuracy. This study will develop an automated model to detect lameness in sheep by analysing the data retrieved from a mounted sensor on the neck of the sheep. This model will help the shepherd to detect lame sheep earlier, to prevent trimming or even culling.
Original languageEnglish
Publication statusPublished - 18 May 2016
EventGraduate School 11th Annual Poster Competition - The University of Northampton
Duration: 18 May 2016 → …

Conference

ConferenceGraduate School 11th Annual Poster Competition
Period18/05/16 → …

Fingerprint

lameness
sensors (equipment)
data analysis
sheep
sawing
culling (animals)
longitude
gait
posture
signs and symptoms (animals and humans)
neck
locomotion
farming systems
farms
monitoring
animals

Cite this

Al-Rubaye, Z. (2016). Lameness detection in sheep through behavioural sensor data analysis. Poster session presented at Graduate School 11th Annual Poster Competition, .
Al-Rubaye, Zainab. / Lameness detection in sheep through behavioural sensor data analysis. Poster session presented at Graduate School 11th Annual Poster Competition, .
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Al-Rubaye, Z 2016, 'Lameness detection in sheep through behavioural sensor data analysis' Graduate School 11th Annual Poster Competition, 18/05/16, .

Lameness detection in sheep through behavioural sensor data analysis. / Al-Rubaye, Zainab.

2016. Poster session presented at Graduate School 11th Annual Poster Competition, .

Research output: Contribution to conference typesPosterResearch

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T1 - Lameness detection in sheep through behavioural sensor data analysis

AU - Al-Rubaye, Zainab

PY - 2016/5/18

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N2 - Lameness is a clinical symptom referring to locomotion changes, resulting in impaired and erratic movements that differ widely from normal gait or posture. Lameness has an adverse impact on both sheep welfare and farm economy, therefore the preclinical detection of lameness will improve both sheep health and, in turn, support farming businesses. A newly developed sensor technology should enable automatic monitoring of animals to determine physiological and behavioural indicators, which would then be subsequently used as inputs into data analysis algorithms. The sensor that will be used to conduct this research is immensely accurate and sensitive. It provides acceleration, angular velocity, orientation, longitude, latitude and the time of reading which can be set up according to the demanded accuracy. This study will develop an automated model to detect lameness in sheep by analysing the data retrieved from a mounted sensor on the neck of the sheep. This model will help the shepherd to detect lame sheep earlier, to prevent trimming or even culling.

AB - Lameness is a clinical symptom referring to locomotion changes, resulting in impaired and erratic movements that differ widely from normal gait or posture. Lameness has an adverse impact on both sheep welfare and farm economy, therefore the preclinical detection of lameness will improve both sheep health and, in turn, support farming businesses. A newly developed sensor technology should enable automatic monitoring of animals to determine physiological and behavioural indicators, which would then be subsequently used as inputs into data analysis algorithms. The sensor that will be used to conduct this research is immensely accurate and sensitive. It provides acceleration, angular velocity, orientation, longitude, latitude and the time of reading which can be set up according to the demanded accuracy. This study will develop an automated model to detect lameness in sheep by analysing the data retrieved from a mounted sensor on the neck of the sheep. This model will help the shepherd to detect lame sheep earlier, to prevent trimming or even culling.

M3 - Poster

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Al-Rubaye Z. Lameness detection in sheep through behavioural sensor data analysis. 2016. Poster session presented at Graduate School 11th Annual Poster Competition, .