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Multimodal Technologies Interact. 2018, 2(2), 27; https://doi.org/10.3390/mti2020027

A Wearable Sensor System for Lameness Detection in Dairy Cattle

1
Lehrstuhl für Angewandte Softwaretechnik, Faculty of Informatics, Technical University Munich, Bolzmannstr 3, 85748 München, Germany
2
Lehr- und Versuchsgut Oberschleißheim, Faculty of Veterinary Medicine, Ludwig Maximilian University, St. Hubertusstraße 12, 85764 München, Germany
This paper is an extended version of our paper published in the Fourth International Conference on Animal-Computer Interaction, Milton Keynes, United Kingdom, 21–23 November 2017.
*
Author to whom correspondence should be addressed.
Received: 17 April 2018 / Revised: 8 May 2018 / Accepted: 8 May 2018 / Published: 15 May 2018
(This article belongs to the Special Issue Multimodal Technologies in Animal–Computer Interaction)
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Abstract

Cow lameness is a common manifestation in dairy cattle that causes severe health and life quality issues to cows, including pain and a reduction in their life expectancy. In our previous work, we introduced an algorithmic approach to automatically detect anomalies in the walking pattern of cows using a wearable motion sensor. In this article, we provide further insights into a system for automatic lameness detection, including the decisions we made when designing the system, the requirements that drove these decisions and provide further insight into the algorithmic approach. Results from a controlled experiment we conducted indicate that our approach can detect deviations in cows’ gait with an accuracy of 91.1%. The information provided by our system can be useful to spot lameness-related diseases automatically and alarm veterinarians. View Full-Text
Keywords: gait analysis; anomaly detection; unsupervised machine learning gait analysis; anomaly detection; unsupervised machine learning
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Haladjian, J.; Haug, J.; Nüske, S.; Bruegge, B. A Wearable Sensor System for Lameness Detection in Dairy Cattle. Multimodal Technologies Interact. 2018, 2, 27.

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