{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T09:49:22Z","timestamp":1774518562685,"version":"3.50.1"},"reference-count":11,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T00:00:00Z","timestamp":1733875200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Internet Technology Letters"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>This study presents an innovative Transformer\u2010based deep learning model for heart rate estimation in wearable devices, addressing accuracy challenges during high\u2010intensity activities. Our model, utilizing self\u2010attention mechanisms and energy\u2010efficient computational strategies, achieves a mean absolute error (MAE) of 4.0\u20134.2 beats per minute and correlation coefficients of 0.92\u20130.93 on public datasets PPG\u2010DaLiA and WESAD. On our more challenging proprietary athlete dataset, the model maintains excellent performance with an MAE of 4.3 beats per minute and a correlation coefficient of 0.91. Ablation studies demonstrate the importance of attention mechanisms, positional encoding, and Gaussian\u2010weighted loss functions to model performance. These results highlight the potential of our approach in improving heart rate monitoring accuracy in wearable technologies, particularly for high\u2010intensity athletic data, showcasing its adaptability and effectiveness in real\u2010world athletic scenarios.<\/jats:p>","DOI":"10.1002\/itl2.631","type":"journal-article","created":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T22:03:27Z","timestamp":1733954607000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["<scp>TransformHR<\/scp>\n                    : A Novel Approach to Athlete Heart Rate Monitoring With Transformer\u2010Based Wearable Technology"],"prefix":"10.1002","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-9010-7221","authenticated-orcid":false,"given":"Yunfeng","family":"Shen","sequence":"first","affiliation":[{"name":"Jilin Sport University  Jilin China"}]}],"member":"311","published-online":{"date-parts":[[2024,12,11]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/itl2.477"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1162\/99608f92.8636cb81"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.103457"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2023.3251110"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2023.3260559"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/s19143079"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13152566"},{"key":"e_1_2_7_9_1","first-page":"5998","volume-title":"Advances in Neural Information Processing Systems","author":"Vaswani A.","year":"2017"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467401"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBCAS.2021.3122017"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3242969.3242985"}],"container-title":["Internet Technology Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/itl2.631","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T12:20:38Z","timestamp":1762777238000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/itl2.631"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,11]]},"references-count":11,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["10.1002\/itl2.631"],"URL":"https:\/\/doi.org\/10.1002\/itl2.631","archive":["Portico"],"relation":{},"ISSN":["2476-1508","2476-1508"],"issn-type":[{"value":"2476-1508","type":"print"},{"value":"2476-1508","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,11]]},"assertion":[{"value":"2024-11-09","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-12-02","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-12-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e631"}}