Predicting Lameness in Sheep Activity Using Tri-Axial Acceleration Signals
نویسندگان
چکیده
منابع مشابه
Predicting Lameness in Sheep Activity Using Tri-Axial Acceleration Signals
Lameness is a clinical symptom associated with a number of sheep diseases around the world, having adverse effects on weight gain, fertility, and lamb birth weight, and increasing the risk of secondary diseases. Current methods to identify lame animals rely on labour intensive visual inspection. The aim of this current study was to determine the ability of a collar, leg, and ear attached tri-ax...
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Physical activity has been associated with health improvements in a number of populations. Step counting is one of the most commonly used measures of physical activity [1]. Due to their small size and light weight, the use of wearable sensors for step counts has been investigated in many studies [2, 3] as they are suitable for home deployment. One of the main issues with step counts as a physic...
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Quantifying activity levels among healthy older adults and patients can provide objective information on sedentary behavior and physical function [1]. In order to accurately quantify activity in the free-living environment, a robust method for classifying posture and activity needs to be established. Therefore, the purpose of this study was to validate the identification of static postures and ...
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This paper proposes a high accuracy classifier for human activity based on data collected with a single tri-axial accelerometer mounted on the right part of the hip. The accuracy of this classifier is very important for detecting the postures. Therefore we use methods like acceleration magnitude and neural network and compare them to find the best solution.
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Background: Coaches in elite swimming carefully design the training programs of their swimmers and are keen on achieving strict adherence to those programs by their athletes. At present, coaches usually monitor the compliance of their swimmers to the training program with a stopwatch. However, this measurement clearly limits the monitoring possibilities and is subject to human error. Therefore,...
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ژورنال
عنوان ژورنال: Animals
سال: 2018
ISSN: 2076-2615
DOI: 10.3390/ani8010012