{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T09:04:50Z","timestamp":1770023090447,"version":"3.49.0"},"reference-count":10,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:00:00Z","timestamp":1768780800000},"content-version":"vor","delay-in-days":18,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Internet Technology Letters"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Traditional cloud\u2010centric architectures face significant challenges when processing high\u2010frequency multimodal data from massive smart devices and smartphone sensors used during motion capture and training. Current approaches also struggle with the low\u2010latency computational demands of various sensors. Edge computing has appeared as a novel way to reduce the processing latency. Hence, to address these challenges, a real\u2010time motion capture method is proposed under the edge computing framework for an AI\u2010assisted sports training strategy. First, an edge computing\u2010based framework is designed to leverage distributed edge resources and lightweight AI models for sensor data capture and training guidance on smartphones. Besides, based on the lightweight Long Short\u2010Term Memory (LSTM) model, we propose a real\u2010time motion capture and AI\u2010assisted sport training strategy. The LSTM is integrated to analyze temporal dependencies in sequential data, which is ideal for capturing motion patterns, while the feedback mechanism is applied to optimize the sports training process iteratively. By comparing the proposed method with recent state\u2010of\u2010the\u2010art approaches, the experimental results demonstrate that our method shows better performance in latency, accuracy, and\n                    <jats:italic>F<\/jats:italic>\n                    1\u2010score.\n                  <\/jats:p>","DOI":"10.1002\/itl2.70220","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T12:24:31Z","timestamp":1768825471000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Real\u2010Time Motion Capture and\n                    <scp>AI<\/scp>\n                    \u2010Assisted Training Strategy Using Edge Computing and Smartphone Sensors"],"prefix":"10.1002","volume":"9","author":[{"given":"Yashan","family":"Zhang","sequence":"first","affiliation":[{"name":"Shenyang Ligong University  Shenyang Liaoning China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenwen","family":"Pan","sequence":"additional","affiliation":[{"name":"Qiqihar University  Qiqihar Heilongjiang China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,1,19]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/LCA.2022.3189207"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3144450"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2021.3122349"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2024.3440050"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3513893"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3555543"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3177442"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3381180"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3327934"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3382832"}],"container-title":["Internet Technology Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/itl2.70220","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/itl2.70220","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/itl2.70220","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T03:40:50Z","timestamp":1769139650000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/itl2.70220"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":10,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["10.1002\/itl2.70220"],"URL":"https:\/\/doi.org\/10.1002\/itl2.70220","archive":["Portico"],"relation":{},"ISSN":["2476-1508","2476-1508"],"issn-type":[{"value":"2476-1508","type":"print"},{"value":"2476-1508","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"2025-06-19","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-02","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-19","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70220"}}