{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T18:35:04Z","timestamp":1783103704905,"version":"3.54.6"},"reference-count":55,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T00:00:00Z","timestamp":1684972800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100015333","name":"Kayamori Foundation of Informational Science Advancement","doi-asserted-by":"publisher","award":["K32XXV562"],"award-info":[{"award-number":["K32XXV562"]}],"id":[{"id":"10.13039\/100015333","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100015333","name":"Kayamori Foundation of Informational Science Advancement","doi-asserted-by":"publisher","award":["FY2020"],"award-info":[{"award-number":["FY2020"]}],"id":[{"id":"10.13039\/100015333","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Tokyo University of Agriculture and Technology","award":["K32XXV562"],"award-info":[{"award-number":["K32XXV562"]}]},{"name":"Tokyo University of Agriculture and Technology","award":["FY2020"],"award-info":[{"award-number":["FY2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Recently, animal welfare has gained worldwide attention. The concept of animal welfare encompasses the physical and mental well-being of animals. Rearing layers in battery cages (conventional cages) may violate their instinctive behaviors and health, resulting in increased animal welfare concerns. Therefore, welfare-oriented rearing systems have been explored to improve their welfare while maintaining productivity. In this study, we explore a behavior recognition system using a wearable inertial sensor to improve the rearing system based on continuous monitoring and quantifying behaviors. Supervised machine learning recognizes a variety of 12 hen behaviors where various parameters in the processing pipeline are considered, including the classifier, sampling frequency, window length, data imbalance handling, and sensor modality. A reference configuration utilizes a multi-layer perceptron as a classifier; feature vectors are calculated from the accelerometer and angular velocity sensor in a 1.28 s window sampled at 100 Hz; the training data are unbalanced. In addition, the accompanying results would allow for a more intensive design of similar systems, estimation of the impact of specific constraints on parameters, and recognition of specific behaviors.<\/jats:p>","DOI":"10.3390\/s23115077","type":"journal-article","created":{"date-parts":[[2023,5,26]],"date-time":"2023-05-26T02:00:19Z","timestamp":1685066419000},"page":"5077","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Evaluating Behavior Recognition Pipeline of Laying Hens Using Wearable Inertial Sensors"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5294-2812","authenticated-orcid":false,"given":"Kaori","family":"Fujinami","sequence":"first","affiliation":[{"name":"Division of Advanced Information Technology and Computer Science, Institute of Engineering, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan"},{"name":"Department of Bio-Functions and Systems Science, Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryo","family":"Takuno","sequence":"additional","affiliation":[{"name":"Department of Bio-Functions and Systems Science, Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Itsufumi","family":"Sato","sequence":"additional","affiliation":[{"name":"Department of Agriculture, Graduate School of Agriculture, Tokyo University of Agriculture and Technology, Tokyo 183-8509, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9136-2976","authenticated-orcid":false,"given":"Tsuyoshi","family":"Shimmura","sequence":"additional","affiliation":[{"name":"Institute of Global Innovation Research, Tokyo University of Agriculture and Technology, Tokyo 183-8509, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,25]]},"reference":[{"key":"ref_1","unstructured":"World Organisation for Animal Health (2023, March 27). 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