A hybrid forecasting model for ageing breast deformation during yoga practice

Jie Zhou, Jianming Chen, Newman Lau, Qian Mao, Zidan Gong, Yang Liu, Joanne Yip, Winnie Yu, Jun Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)


In this work, the deformation of bilateral breasts was investigated with an established hybrid model to predict the nipple movement specifically for senior women during yoga exercise. A motion capture system was used to collect the displacement of 10 markers on the breasts from 11 senior women (average age of 62) during yoga practice and then the data were analyzed by integrating the absolute grey relation analysis (AGRA) and extreme learning machine (ELM). The right and left breasts had the maximum motion amplitude in the horizontal direction but they were respectively featured with contraction and extension during yoga practice. AGRA showed that the nipple motion was highly associated with the vertical region above the nipple for the left breast but the parallel region along with the nipple for the right breast. The ELM model is able to predict the nipple movement within tolerable error (∼0.0037). This study lays a foundation for a better understanding of ageing breast kinematics during yoga poses with limited practical experiments. Besides, the accurate and efficient results can be used not only for yoga pose instruction but also for ergonomic sports bra design.

Original languageEnglish
Pages (from-to)974-984
Number of pages11
JournalTextile Research Journal
Issue number7-8
Publication statusPublished - Apr 2022


  • breasts
  • deformations
  • kinematics
  • prediction
  • Senior women

ASJC Scopus subject areas

  • Chemical Engineering (miscellaneous)
  • Polymers and Plastics


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