- 【Updated on May 12, 2025】 Integration of CiNii Dissertations and CiNii Books into CiNii Research
- Trial version of CiNii Research Knowledge Graph Search feature is available on CiNii Labs
- Suspension and deletion of data provided by Nikkei BP
- Regarding the recording of “Research Data” and “Evidence Data”
The Optimal Posture Estimation for Training Pelvic Floor Muscles by Using Individualized Musculoskeletal Model
-
- WAKAIKI Tomohiro
- Hokkaido University
-
- TANAKA Takayuki
- Hokkaido University
-
- SHIMATANI Koji
- Prefectural University of Hiroshima
-
- KURITA Yuichi
- Hiroshima University
-
- SUGIYAMA Yoshimi
- Hashimoto Gynecological Clinic
Bibliographic Information
- Other Title
-
- 個人適合した筋骨格モデルを用いた骨盤底筋強化のための最適姿勢導出
Search this article
Description
<p>SUI (Stress Urinary Incontinence) is a typical quality of life disease in women, and it can cause symptoms of unexpected urine leaks when abdominal pressure rises, such as coughing and sneezing. It is mainly caused by relaxation or damage of PFM (Pelvic Floor Muscles) due to obesity, aging and childbirth and it is considered that strengthening of PFM is effective for prevention. Training methods such as Kegel gymnastics have been devised so far, but these methods need expert guidance and time for training. Individual differences of pelvis shape and alignment affect to the effect of training PFMs. In order to solve this problem, we proposed a method to estimate the individual optimal training posture, by defining 11 postures that can be taken in daily life and calculating the PFM activation of each posture with the individualized musculoskeletal model. Moreover, the proposed method was evaluated by comparing with the measured values of PFM activation in each posture. As a result, a positive correlation with the calculation result was confirmed in 3 subjects out of 6, suggesting the validity of this method.</p>
Journal
-
- Biomechanisms
-
Biomechanisms 25 (0), 113-124, 2020
Society of Biomechanisms
- Tweet
Details 詳細情報について
-
- CRID
- 1390007237335483904
-
- NII Article ID
- 130008065573
-
- ISSN
- 1349497X
- 13487116
-
- Text Lang
- ja
-
- Article Type
- journal article
-
- Data Source
-
- JaLC
- Crossref
- CiNii Articles
- KAKEN
- OpenAIRE
-
- Abstract License Flag
- Disallowed