Dog behaviour classification with movement sensors placed on the harness and the collar

Pekka Kumpulainen, Anna Valldeoriola Cardó, Sanni Somppi, Heini Törnqvist, Heli Väätäjä, Päivi Majaranta, Yulia Gizatdinova, Christoph Hoog Antink, Veikko Surakka, Miiamaaria V. Kujala, Outi Vainio, Antti Vehkaoja

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Abstract

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. The data used in this article as well as the signal processing scripts are openly available in Mendeley Data, https://doi.org/10.17632/vxhx934tbn.1.

Original languageEnglish
Article number105393
Number of pages7
JournalAPPLIED ANIMAL BEHAVIOUR SCIENCE
Volume241
DOIs
Publication statusPublished - 1 Jul 2021
Publication typeA1 Journal article-refereed

Keywords

  • Accelerometry
  • Actigraphy
  • Activity monitoring
  • Behaviour classification
  • Canine
  • Dog
  • Wearable technology

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Food Animals
  • Animal Science and Zoology

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