Development of fully fashioned knitted spacer fabric bra cup: one-step production from yarn

Yu, Annie; Shirakihara, Miwa; Yick, Kit Lun; Sukigara, Sachiko; CHAN, Kam-ching

doi:10.1016/j.matdes.2022.110825

Cited by 3 publications

(1 citation statement)

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“…The breast motion data of 22 mature female participants were collected by using a motion capture system (Eagle, Motion Analysis Corporation, Santa Rosa, CA, USA) at a sampling rate of 90 Hz. This system is popular and reliable for studies related to bra design and breast motion evaluation [39][40][41][42]. Thirteen spherical retro-reflective markers were attached on the left breast of the subject (see Figure 2).…”

Section: Breast Motion Data Collectionmentioning

confidence: 99%

A Systematic Analysis of 3D Deformation of Aging Breasts Based on Artificial Neural Networks

Zhang

Liang²,

Lau

et al. 2022

IJERPH

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The measurement and prediction of breast skin deformation are key research directions in health-related research areas, such as cosmetic and reconstructive surgery and sports biomechanics. However, few studies have provided a systematic analysis on the deformations of aging breasts. Thus, this study has developed a model order reduction approach to predict the real-time strain of the breast skin of seniors during movement. Twenty-two women who are on average 62 years old participated in motion capture experiments, in which eight body variables were first extracted by using the gray relational method. Then, backpropagation artificial neural networks were built to predict the strain of the breast skin. After optimization, the R-value for the neural network model reached 0.99, which is within acceptable accuracy. The computer-aided system of this study is validated as a robust simulation approach for conducting biomechanical analyses and predicting breast deformation.

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Section: Breast Motion Data Collectionmentioning

confidence: 99%