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Due to spectral leakage caused by respiratory motion and the difficulty in capturing subtle mechanical motions within a single heartbeat cycle, detection and segmentation often suffer from temporal boundary ambiguity and critical event omission. To address these issues, we propose an innovative millimeter-wave (mmWave) fine-grained cardiac event detection and segmentation system that integrates a multi-scale boundary enhancement framework. This framework consists of a multi-scale context fusion module and a boundary-aware enhancement module, which collaboratively mitigate respiratory motion interference and improve feature recognition capabilities. Through dedicated training, our system captures both multi-scale local details and global relationships, enabling user-independent detection and segmentation without the need for subject-specific calibration. The experiments in outpatient of a hospital involving 4,339 participants, including participants with conditions such as Bundle Branch Block (BBB), First-Degree Atrioventricular Block (I-AVB), and T wave abnormalities (T abn.) show that the proposed system achieves an F1 score of 90.6%, outperforming baseline methods, and simultaneously achieves an average estimation error of 14.9 milliseconds for cardiac event intervals, representing a reduction of 5.1 milliseconds compared to the baseline error. The results demonstrate that this system can robustly detect fine-grained cardiac events, thereby providing a more reliable technical foundation for early cardiovascular monitoring.<\/jats:p>","DOI":"10.1145\/3749457","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T17:15:45Z","timestamp":1756919745000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Contactless Fine-grained Cardiac Events Detection and Segmentation with Radio Frequency Signals"],"prefix":"10.1145","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0660-0958","authenticated-orcid":false,"given":"Zehan","family":"Guo","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7164-5127","authenticated-orcid":false,"given":"Binbin","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4532-3236","authenticated-orcid":false,"given":"Jinbo","family":"Chen","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0379-1525","authenticated-orcid":false,"given":"Yang","family":"Hu","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3227-4562","authenticated-orcid":false,"given":"Yan","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,9,3]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Cardiovascular diseases (cvds). https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/cardiovascular-diseases-(cvds)","author":"World Health Organization","year":"2024","unstructured":"World Health Organization. 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