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However, traditional HAR methods solely focus on identifying user movements, lacking interactivity and user engagement. This paper proposes a novel immersive HAR method called MovPosVR. Virtual reality (VR) technology is employed to create realistic scenes and enhance the user experience. To improve the accuracy of user action recognition in immersive HAR, a multi\u2010scale spatio\u2010temporal attention network (MSSTANet) is proposed. The network combines the convolutional residual squeeze and excitation (CRSE) module with the multi\u2010branch convolution and long short\u2010term memory (MCLSTM) module to extract spatio\u2010temporal features and automatically select relevant features from action signals. Additionally, a multi\u2010head attention with shared linear mechanism (MHASLM) module is designed to facilitate information interaction, further enhancing feature extraction and improving accuracy. The MSSTANet network achieves superior performance, with accuracy rates of 99.33% and 98.83% on the publicly available WISDM and PAMPA2 datasets, respectively, surpassing state\u2010of\u2010the\u2010art networks. Our method showcases the potential to display user actions and position information in a virtual world, enriching user experiences and interactions across diverse application scenarios.<\/jats:p>","DOI":"10.1002\/cav.2293","type":"journal-article","created":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T03:44:27Z","timestamp":1727149467000},"update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Human action recognition in immersive virtual reality based on multi\u2010scale spatio\u2010temporal attention network"],"prefix":"10.1002","volume":"35","author":[{"ORCID":"http:\/\/orcid.org\/0009-0005-1550-1531","authenticated-orcid":false,"given":"Zhiyong","family":"Xiao","sequence":"first","affiliation":[{"name":"School of Computer Science and Artificial Intelligence Wuhan Textile University Wuhan China"}]},{"given":"Yukun","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science and 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