ArticleData in brief2022
Description of movement sensor dataset for dog behavior classification.
Article in Data in brief, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Refining Accelerometer-Based Animal Behaviour Classifications With Sequence-Informed Post-Processing.Ecology and evolution · 2026Article
- A benchmark for computational analysis of animal behavior, using animal-borne tags.Movement ecology · 2024Article
- Automated Pipeline for Robust Cat Activity Detection Based on Deep Learning and Wearable Sensor Data.Sensors (Basel, Switzerland) · 2024Article
- A non-invasive method to determine core temperature for cats and dogs using surface temperatures based on machine learning.BMC veterinary research · 2024Article
- TN-GAN-Based Pet Behavior Prediction through Multiple-Dimension Time-Series Augmentation.Sensors (Basel, Switzerland) · 2023Article
- Article
- Description of movement sensor dataset for dog behavior classification.Data in brief · 2022Article
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Authors and funding
10 authors.
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Abstract
Movement sensor data from seven static and dynamic dog behaviors (sitting, standing, lying down, trotting, walking, playing, and (treat) searching i.e. sniffing) was collected from 45 middle to large sized dogs with six degree-of-freedom movement sensors attached to the collar and the harness. With 17 dogs the collection procedure was repeated. The duration of each of the seven behaviors was approximately three minutes. The order of the tasks was varied between the dogs and the two repetitions (for the 17 dogs). The behaviors were annotated post-hoc based on the video recordings made with two camcorders during the tests with one second resolution. The annotations were accurately synchronized with the raw movement sensors data. The annotated data was originally used for training behavior classification machine learning algorithms for classifying the seven behaviors. The developed signal processing and classification algorithms are provided together with the raw measurement data and reference annotations. The description and results of the original investigation that the dataset relates to are found in: P. Kumpulainen, A. Valldeoriola Cardó, S. Somppi, H. Törnqvist, H. Väätäjä, P. Majaranta, Y. Gizatdinova, C. Hoog Antink, V. Surakka, M. V. Kujala, O. Vainio, A. Vehkaoja, Dog behavior classification with movement sensors placed on the harness and the collar, Applied Animal behavior Science, 241 (2021), 105,393.
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