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Description of movement sensor dataset for dog behavior classification
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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777071/ https://www.ncbi.nlm.nih.gov/pubmed/35079615 http://dx.doi.org/10.1016/j.dib.2022.107822 |
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author | Vehkaoja, Antti Somppi, Sanni Törnqvist, Heini Valldeoriola Cardó, Anna Kumpulainen, Pekka Väätäjä, Heli Majaranta, Päivi Surakka, Veikko Kujala, Miiamaaria V. Vainio, Outi |
author_facet | Vehkaoja, Antti Somppi, Sanni Törnqvist, Heini Valldeoriola Cardó, Anna Kumpulainen, Pekka Väätäjä, Heli Majaranta, Päivi Surakka, Veikko Kujala, Miiamaaria V. Vainio, Outi |
author_sort | Vehkaoja, Antti |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8777071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-87770712022-01-24 Description of movement sensor dataset for dog behavior classification Vehkaoja, Antti Somppi, Sanni Törnqvist, Heini Valldeoriola Cardó, Anna Kumpulainen, Pekka Väätäjä, Heli Majaranta, Päivi Surakka, Veikko Kujala, Miiamaaria V. Vainio, Outi Data Brief Data Article 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. Elsevier 2022-01-11 /pmc/articles/PMC8777071/ /pubmed/35079615 http://dx.doi.org/10.1016/j.dib.2022.107822 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Vehkaoja, Antti Somppi, Sanni Törnqvist, Heini Valldeoriola Cardó, Anna Kumpulainen, Pekka Väätäjä, Heli Majaranta, Päivi Surakka, Veikko Kujala, Miiamaaria V. Vainio, Outi Description of movement sensor dataset for dog behavior classification |
title | Description of movement sensor dataset for dog behavior classification |
title_full | Description of movement sensor dataset for dog behavior classification |
title_fullStr | Description of movement sensor dataset for dog behavior classification |
title_full_unstemmed | Description of movement sensor dataset for dog behavior classification |
title_short | Description of movement sensor dataset for dog behavior classification |
title_sort | description of movement sensor dataset for dog behavior classification |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777071/ https://www.ncbi.nlm.nih.gov/pubmed/35079615 http://dx.doi.org/10.1016/j.dib.2022.107822 |
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