Horsing Around: A Dataset Comprising Horse Movement

Jacob W. Kamminga; Lara Janßen; Nirvana  Meratnia; Paul J.M. Havinga

doi:10.3390/data4040131

Horsing Around: A Dataset Comprising Horse Movement

Jacob W. Kamminga^*, Lara Janßen, Nirvana Meratnia, Paul J.M. Havinga

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

14 Citations (Scopus)

177 Downloads (Pure)

Abstract

Movement data were collected at a riding stable over seven days. The dataset comprises data from 18 individual horses and ponies with 1.2 million 2-s data samples, of which 93,303 samples have been tagged with labels (labeled data). Data from 11 subjects were labeled. The data from six subjects and six activities were labeled more extensively. Data were collected during horse riding sessions and when the horses freely roamed the pasture over seven days. Sensor devices were attached to a collar that was positioned around the neck of horses. The orientation of the sensor devices was not strictly fixed. The sensors devices contained a three-axis accelerometer, gyroscope, and magnetometer and were sampled at 100 Hz.

Original language	English
Article number	131
Journal	Data
Volume	4
Issue number	4
Early online date	22 Sept 2019
DOIs	https://doi.org/10.3390/data4040131
Publication status	Published - Dec 2019

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10.3390/data4040131Licence: CC BY

data-04-00131Final published version, 9.4 MBLicence: CC BY

Horsing Around -- A Dataset Comprising Horse Movement
Kamminga, J. W. (Creator), 4TU.Centre for Research Data, 14 Aug 2019
DOI: 10.4121/uuid:2e08745c-4178-4183-8551-f248c992cb14
Dataset

14 Citations
1 Conference contribution
1 PhD Thesis - Research UT, graduation UT

Improving the Annotation Efficiency for Animal Activity Recognition using Active Learning
Spink, S., Kamminga, J. W. & Kamilaris, A., 18 May 2022, Measuring Behavior 2022: 12th International Conference on Methods and Techniques in Behavioral Research, and 6th Seminar on Behavioral Methods. Spink, A., Barski, J., Brouwer, A.-M., Riedel, G. & Sil, A. (eds.). Vol. 2. p. 51-58 8 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Open Access
File
90 Downloads (Pure)
Hiding in the Deep: Online Animal Activity Recognition using Motion Sensors and Machine Learning
Kamminga, J. W., 9 Sept 2020, Enschede: University of Twente. 225 p.
Research output: Thesis › PhD Thesis - Research UT, graduation UT

Open Access
File
950 Downloads (Pure)

Cite this

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title = "Horsing Around: A Dataset Comprising Horse Movement",

abstract = "Movement data were collected at a riding stable over seven days. The dataset comprises data from 18 individual horses and ponies with 1.2 million 2-s data samples, of which 93,303 samples have been tagged with labels (labeled data). Data from 11 subjects were labeled. The data from six subjects and six activities were labeled more extensively. Data were collected during horse riding sessions and when the horses freely roamed the pasture over seven days. Sensor devices were attached to a collar that was positioned around the neck of horses. The orientation of the sensor devices was not strictly fixed. The sensors devices contained a three-axis accelerometer, gyroscope, and magnetometer and were sampled at 100 Hz.",

author = "Kamminga, {Jacob W.} and Lara Jan{\ss}en and Nirvana Meratnia and Havinga, {Paul J.M.}",

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AU - Janßen, Lara

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AB - Movement data were collected at a riding stable over seven days. The dataset comprises data from 18 individual horses and ponies with 1.2 million 2-s data samples, of which 93,303 samples have been tagged with labels (labeled data). Data from 11 subjects were labeled. The data from six subjects and six activities were labeled more extensively. Data were collected during horse riding sessions and when the horses freely roamed the pasture over seven days. Sensor devices were attached to a collar that was positioned around the neck of horses. The orientation of the sensor devices was not strictly fixed. The sensors devices contained a three-axis accelerometer, gyroscope, and magnetometer and were sampled at 100 Hz.

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ER -

Horsing Around: A Dataset Comprising Horse Movement

Abstract

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Datasets

Horsing Around -- A Dataset Comprising Horse Movement

Research output

Improving the Annotation Efficiency for Animal Activity Recognition using Active Learning

Hiding in the Deep: Online Animal Activity Recognition using Motion Sensors and Machine Learning

Cite this