Estimating Co-Contraction Activation of Trunk Muscles Using a Novel Musculoskeletal Model for Pregnant Women
Source abstract
Abstract
Weight gain and stretched abdominal muscles from an enlarged gravid uterus are remarkable features during pregnancy. These changes elicit postural instability and place strain on body segments, contributing to lower back pain. In general, the agonist and antagonist muscles act simultaneously to increase joint stabilization; however, this can cause additional muscle stress during movement. Furthermore, this activation can be observed in pregnant women because of their unstable body joints. Hence, physical modalities based on assessments of muscle activation are useful for managing low back pain during pregnancy. Musculoskeletal models are common when investigating muscle load. However, it is difficult to apply such models to pregnant women and estimate the co-contraction of muscles using musculoskeletal models. Therefore, the purpose of this study is to construct a musculoskeletal model for pregnant women that estimates the co-contraction of trunk muscles. First, motion analysis was conducted on a pregnant woman and the muscle activations of the rectus abdominis and erector spinae were measured. Then, the musculoskeletal model was specifically modified for pregnant women. Finally, the co-contraction was estimated from the results of the musculoskeletal model and electromyography data using a genetic algorithm. With the proposed methods, weakened abdominal muscle torque and the co-contraction activation of trunk muscles were estimated successfully.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Pregnancy-related medical research · Musculoskeletal pain and rehabilitation · Occupational Health and Performance
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Science for Open and Environmental Systems, Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan
Department of System Design Engineering, Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan
References (32)
Show source-provided references
1. Musculoskeletal disorders of pregnancy, delivery and postpartum10.1016/j.pmr.2007.05.005 ↗
2. Low-back-pain in pregnancy—Abdominal muscles, sit-up performance, and back pain10.1097/00007632-199001000-00008 ↗
3. Effectiveness of maternity support belts in reducing low back pain during pregnancy: A review10.1111/j.1365-2702.2008.02749.x ↗
4. Pregnancy-related low back pain10.3928/01477447-20071001-14 ↗
5. Low back pain and pelvic girdle pain in pregnancy10.5435/JAAOS-D-14-00248 ↗
6. Pregnancy-related pelvic girdle pain (PPP), I: Terminology, clinical presentation, and prevalence10.1007/s00586-003-0615-y ↗
7. Gait in pregnancy-related pelvic girdle pain: Amplitudes, timing, and coordination of horizontal trunk rotations10.1007/s00586-008-0703-0 ↗
8. Three-dimensional motion patterns during active bending in patients with chronic low back pain10.1097/00007632-200209010-00012 ↗
9. Effects of pelvic asymmetry and low back pain on trunk kinematics during sitting: A comparison with standing10.1097/01.brs.0000201325.89493.5f ↗
10. Musculoskeletal aspects of pregnancy10.1097/01.PHM.0000156970.96219.48 ↗
11. Two strategies of transferring from sit-to-stand; the activation of monoarticular and biarticular muscles10.1016/0021-9290(94)90039-6 ↗
12. Quantitative assessment of co-contraction at the ankle joint in walking
13. The internal model and the leading joint hypothesis: Implications for control of multi-joint movements10.1007/s00221-005-2339-1 ↗
14. Musculoskeletal modelling in sports—Evaluation of different software tools with focus on swimming10.1016/j.proeng.2016.06.278 ↗
15. Blache, Y., and Begon, M. (2017). Influence of shoulder kinematic estimate on joint and muscle mechanics predicted by musculoskeletal model. IEEE Trans. Biomed. Eng.10.1109/TBME.2017.2716186 ↗
16. Full-body musculoskeletal model for muscle-driven simulation of human gait10.1109/TBME.2016.2586891 ↗
17. An analysis of muscle load on the erector spinae of a pregnant woman10.1299/jbse.5.357 ↗
18. Consistency among musculoskeletal models: Caveat utilitor10.1007/s10439-013-0843-1 ↗
19. Emg assisted optimization—A hybrid approach for estimating muscle forces in an indeterminate biomechanical model10.1016/0021-9290(94)90282-8 ↗
20. A biomechanical comparison between expert and novice manual materials handlers using a multi-joint emg-assisted optimization musculoskeletal model of the lumbar spine10.1016/j.jbiomech.2016.07.009 ↗
21. Oyong, A.W., Parasuraman, S., and Jauw, V.L. (December, January 30). Robot assisted stroke rehabilitation: Estimation of muscle force /joint torque from EMG using GA. Proceedings of the 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences, Kuala Lumpur, Malaysia.10.1109/IECBES.2010.5742257 ↗
22. Leg muscle activation patterns of sit-to-stand movement in stroke patients10.1097/01.PHM.0000104665.34557.56 ↗
23. EMG activity normalization for trunk muscles in subjects with and without back pain10.1097/00005768-200207000-00005 ↗
24. Shippen, J., and May, B. (2016, January 20–22). Bob—Biomechanics in matlab. Proceedings of the 11th International Conference BIOMDOLE 2016, Druskininkai, Lithuania.10.3846/biomdlore.2016.02 ↗
25. Shippen, J., and May, B. (2013). Teaching Biomechanical Analysis Using Matlab/Simulink, Coventry University.
26. Life and Welfare Technology Center (2017, June 06). “Human Characteristics Database”, Human Characteristics Database, Available online: http://www.tech.nite.go.jp/human/indexeng.html.
27. Examination of mass and location of the center of gravity of segment of the body in Japanese women
28. Basic study on designing maternity wear corresponding to change of body form in the later stage of pregnancy (Part 1): Experimental study on suitability of maternity dress
29. Estimation of inertial parameters of the lower trunk in pregnant japanese women: A longitudinal comparative study and application to motion analysis10.1016/j.apergo.2016.02.010 ↗
30. Madgwick, S.O.H., Harrison, A.J.L., and Vaidyanathan, R. (2011). Estimation of imu and marg orientation using a gradient descent algorithm. Int. Conf. Rehabil. Robot.10.1109/ICORR.2011.5975346 ↗
31. Theeffectiveness of complementary manual therapies for pregnancy-related back and pelvic pain: A systematic review with meta-analysis10.1097/MD.0000000000004723 ↗
32. Patterned electromyographic activity in the sit-to-stand movement10.1016/S1388-2457(99)00109-1 ↗