Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 409264
Title Recording and analysis of locomotion in dairy cows with 3D accelerometers
Author(s) Mol, R.M. de; Lammers, R.J.H.; Pompe, J.C.A.M.; Ipema, A.H.; Hogewerf, P.H.
Source In: Precision Livestock Farming '09, 4th European conference on precision livestock farming, Wageningen, The Netherlands, 6-8 July 2009. - Wageningen : Wageningen Academic Publishers - ISBN 9789086861125 - p. 333 - 341.
Event Wageningen : Wageningen Academic Publishers - ISBN 9789086861125 Precision Livestock Farming '09, Wageningen, The Netherlands, 2009-07-06/2009-07-08
Department(s) Livestock Research
ATV Farm Technology
Publication type Contribution in proceedings
Publication year 2009
Abstract An automated method for lameness detection can be an alternative for detection by regular observations. Accelerometers attached to a leg of the dairy cow can be used to record the locomotion of a dairy cow. In an experiment the 3D acceleration of the right hind leg during walking of three dairy cows was measured and analysed. Nodes with a 3D accelerometer in a wireless sensor network were applied to measure with a frequency of 50 Hz. After data filtering, the data analysis was in two steps: first step detection and secondly the determination of step parameters. Variance analysis was used for step detection. For each step the parameters step length and step time were calculated. The steps and step parameters can be used in future research for gait analysis of lame and non-lame cows. The aim of this paper is to describe the collection and analysis of data in this experiment and to assess the possibilities for gait analysis. It can be concluded that the application of accelerometers in a wireless sensor network gives promising results. Step detection is possible and step parameters can be derived.
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