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This article presents a skeleton\u2010guided action recognition framework with multistream 3D convolutional neural network. Two parallel dual\u2010stream lightweight networks are proposed to enhance the feature extraction ability of human action and meanwhile reduce computation. Two different modes of skeleton input video are constructed to improve the recognition accuracy by decision fusion. The backbone networks adopt Resnet\u201018, the feature fusion layer and sliding window mechanism are both designed, and two cross\u2010entropy losses are used to supervise their training. A dataset (named elder care action recognition (EC\u2010AR)) with different categories of action is built. The experimental results on HMDB\u201051 and EC\u2010AR datasets both demonstrate that the proposed framework outperforms the existing methods. The developed method is also applied to a prototype of elderly\u2010care robots, and the test results in home scenarios show that it still has high recognition accuracy and good real\u2010time performance.<\/jats:p>","DOI":"10.1002\/aisy.202300326","type":"journal-article","created":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T22:59:53Z","timestamp":1695337193000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Skeleton\u2010Guided Action Recognition with Multistream 3D Convolutional Neural Network for Elderly\u2010Care Robot"],"prefix":"10.1002","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9302-9368","authenticated-orcid":false,"given":"Dawei","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Computer and Artificial Intelligence Zhengzhou Univerity  Zhengzhou Henan 450001 China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4084-5644","authenticated-orcid":false,"given":"Yanming","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering Zhengzhou Univerity  Zhengzhou Henan 450001 China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8701-4999","authenticated-orcid":false,"given":"Meng","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence Zhengzhou Univerity  Zhengzhou Henan 450001 China"}]}],"member":"311","published-online":{"date-parts":[[2023,9,21]]},"reference":[{"key":"e_1_2_9_2_1","first-page":"3200","volume":"45","author":"Sun Z.","year":"2022","journal-title":"IEEE Trans. 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