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JRM Vol.30 No.6 pp. 991-1003
doi: 10.20965/jrm.2018.p0991
(2018)

Paper:

Individualization of Musculoskeletal Model for Analyzing Pelvic Floor Muscles Activity Based on Gait Motion Features

Tomohiro Wakaiki*, Takayuki Tanaka*, Koji Shimatani**, Yuichi Kurita***, and Tadayuki Iida**

*Hokkaido University
Kita 14, Nishi 9, Kita-ku, Sapporo, Hokkaido 060-00814, Japan

**Prefectural University of Hiroshima
1-1 Gakuen-machi, Mihara City, Hiroshima 723-0053, Japan

***Hiroshima University
1-4-1 Kagamiyama, Higashihiroshima, Hiroshima 739-8527, Japan

Received:
June 4, 2018
Accepted:
November 8, 2018
Published:
December 20, 2018
Keywords:
individualization, musculoskeletal model, pelvis
Abstract

Stress urinary incontinence (SUI) is a typical quality of life disease in women. The strengthening of the pelvic floor muscle (PFM) is considered effective to prevent this. Specifically, PFM activity is affected by individual pelvic shape and posture. Therefore, it is necessary to analyze muscle activity by considering the individual differences. In this study, individual pelvic alignment was estimated from the feature values of natural gait via multiple regression analysis. In addition, individual pelvic feature points were derived from X-ray images and used to deform the standard model to obtain individual pelvic shapes. Results indicate that the residual averages of the estimated feature angles were less than 2° in most cases. Subsequently, measurements of the pelvis were obtained via MRI to evaluate the estimated pelvis shape. The results indicate that individual adaptation leads to muscle attachment positions, which are important in the muscle activity analysis, and closer to the true MRI value when compared to that of the standard pelvic model.

Pelvis individualization method

Pelvis individualization method

Cite this article as:
T. Wakaiki, T. Tanaka, K. Shimatani, Y. Kurita, and T. Iida, “Individualization of Musculoskeletal Model for Analyzing Pelvic Floor Muscles Activity Based on Gait Motion Features,” J. Robot. Mechatron., Vol.30 No.6, pp. 991-1003, 2018.
Data files:
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