Dog behaviour classification with movement sensors placed on the harness and the collar
Kumpulainen, P., Cardó, A. V., Somppi, S., Törnqvist, H., Väätäjä, H., Majaranta, P., Gizatdinova, Y., Hoog, A. C., Surakka, V., Kujala, M. V., Vainio, O., & Vehkaoja, A. (2021). Dog behaviour classification with movement sensors placed on the harness and the collar. Applied Animal Behaviour Science, 241, Article 105393. https://doi.org/10.1016/j.applanim.2021.105393
Published inApplied Animal Behaviour Science
© 2021 The Authors. Published by Elsevier B.V.
Dog owners’ understanding of the daily behaviour of their dogs may be enhanced by movement measurements that can detect repeatable dog behaviour, such as levels of daily activity and rest as well as their changes. The aim of this study was to evaluate the performance of supervised machine learning methods utilising accelerometer and gyroscope data provided by wearable movement sensors in classification of seven typical dog activities in a semi-controlled test situation. Forty-five middle to large sized dogs participated in the study. Two sensor devices were attached to each dog, one on the back of the dog in a harness and one on the neck collar. Altogether 54 features were extracted from the acceleration and gyroscope signals divided in two-second segments. The performance of four classifiers were compared using features derived from both sensor modalities. and from the acceleration data only. The results were promising; the movement sensor at the back yielded up to 91 % accuracy in classifying the dog activities and the sensor placed at the collar yielded 75 % accuracy at best. Including the gyroscope features improved the classification accuracy by 0.7–2.6 %, depending on the classifier and the sensor location. The most distinct activity was sniffing, whereas the static postures (lying on chest, sitting and standing) were the most challenging behaviours to classify, especially from the data of the neck collar sensor. ...
Dataset(s) related to the publicationhttp://dx.doi.org/10.17632/vxhx934tbn.1
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Additional information about fundingThis research was funded by Business Finland, a Finnish national research funding organization, grant numbers 1665/31/2016, 1894/31/2016, 7244/31/2016 in the context of “Buddy and the Smiths 2.0” project.
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