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To achieve this, a novel nonlinear multi-component dynamic finite element method (FEM) has been established, which uses experimental data obtained via 4D scanning technology and a motion capture system. The data are used to construct a geometric model that comprises the rigid body, layers of soft tissues, skin, pectoralis major muscle, fat, ligaments and glandular tissues. The traditional point-to-point method has a relative mean absolute error of less than 7.92% while the latest surface-to-surface method has an average Euclidean distance (<jats:italic>d<\/jats:italic>) of 7.05\u00a0mm, validating the simulated results. After simulating the motion of the different components of the breasts, the displacement analysis confirms that when the motion reaches the moment of largest displacement, the displacement of the breast components is proportional to their distance from the chest wall. A biomechanical analysis indicates that the stress sustained by the breast components in ascending order is the glandular tissues, pectoralis major muscle, adipose tissues, and ligaments. The ligaments provide the primary support during motion, followed by the pectoralis major muscle. In addition, specific stress points of the breast components are identified. The stiffness impact experiment indicates that compared with ligaments, the change of glandular tissue stiffness had a slightly more obvious effect on the breast surface. The findings serve as a valuable reference for the medical field and sports bra industry to enhance breast protection during motion.<\/jats:p>","DOI":"10.1007\/s10237-024-01862-2","type":"journal-article","created":{"date-parts":[[2024,5,28]],"date-time":"2024-05-28T22:01:43Z","timestamp":1716933703000},"page":"1679-1694","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Construction of multi-component finite element model to predict biomechanical behaviour of breasts during running and quantification of the stiffness impact of internal structure"],"prefix":"10.1007","volume":"23","author":[{"given":"Jiazhen","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qilong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joanne","family":"Yip","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9043-1781","authenticated-orcid":false,"given":"Kit-lun","family":"Yick","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,28]]},"reference":[{"issue":"2","key":"1862_CR1","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1177\/1754337112440644","volume":"226","author":"JVDB Antonie","year":"2012","unstructured":"Antonie JVDB, Maarten H, Heiko S, Berthold K (2012) Predictive musculoskeletal simulation using optimal control: effects of added limb mass on energy cost and kinematics of walking and running. 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