Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals
Abstract Muscle synergy analysis is useful for investigating trunk coordination patterns based on the assumption that the central nervous system reduces the dimensionality of muscle activation to simplify movement. This study aimed to quantify the variability in trunk muscle synergy during various t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-28467-6 |
| _version_ | 1797945929704144896 |
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| author | Hiroki Saito Hikaru Yokoyama Atsushi Sasaki Kazuya Matsushita Kimitaka Nakazawa |
| author_facet | Hiroki Saito Hikaru Yokoyama Atsushi Sasaki Kazuya Matsushita Kimitaka Nakazawa |
| author_sort | Hiroki Saito |
| collection | DOAJ |
| description | Abstract Muscle synergy analysis is useful for investigating trunk coordination patterns based on the assumption that the central nervous system reduces the dimensionality of muscle activation to simplify movement. This study aimed to quantify the variability in trunk muscle synergy during various trunk motor tasks in healthy participants to provide reference data for evaluating trunk control strategies in patients and athletes. Sixteen healthy individuals performed 11 trunk movement and stability tasks with electromyography (EMG) recording of their spinal and abdominal muscles (6 bilaterally). Non-negative matrix factorization applied to the concatenated EMG of all tasks identified the five trunk muscle synergies (W) with their corresponding temporal patterns (C). The medians of within-cluster similarity defined by scalar products in W and rmax coefficient using the cross-correlation function in C were 0.73–0.86 and 0.64–0.75, respectively, while the inter-session similarities were 0.81–0.96 and 0.74–0.84, respectively. However, the lowest and highest values of both similarity indices were broad, reflecting the musculoskeletal system’s redundancy within and between participants. Furthermore, the significant differences in the degree of variability between the trunk synergies may represent the different neural features of synergy organization and strategies to overcome the various mechanical demands of a motor task. |
| first_indexed | 2024-04-10T21:03:55Z |
| format | Article |
| id | doaj.art-1a69a67661fd484680e2138abb9a90f9 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-10T21:03:55Z |
| publishDate | 2023-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-1a69a67661fd484680e2138abb9a90f92023-01-22T12:08:52ZengNature PortfolioScientific Reports2045-23222023-01-0113111210.1038/s41598-023-28467-6Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individualsHiroki Saito0Hikaru Yokoyama1Atsushi Sasaki2Kazuya Matsushita3Kimitaka Nakazawa4Department of Life Sciences, Graduate School of Arts and Sciences, The University of TokyoInstitute of Engineering, Tokyo University of Agriculture and TechnologyDepartment of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka UniversityAobadai Takeda OrthopedicDepartment of Life Sciences, Graduate School of Arts and Sciences, The University of TokyoAbstract Muscle synergy analysis is useful for investigating trunk coordination patterns based on the assumption that the central nervous system reduces the dimensionality of muscle activation to simplify movement. This study aimed to quantify the variability in trunk muscle synergy during various trunk motor tasks in healthy participants to provide reference data for evaluating trunk control strategies in patients and athletes. Sixteen healthy individuals performed 11 trunk movement and stability tasks with electromyography (EMG) recording of their spinal and abdominal muscles (6 bilaterally). Non-negative matrix factorization applied to the concatenated EMG of all tasks identified the five trunk muscle synergies (W) with their corresponding temporal patterns (C). The medians of within-cluster similarity defined by scalar products in W and rmax coefficient using the cross-correlation function in C were 0.73–0.86 and 0.64–0.75, respectively, while the inter-session similarities were 0.81–0.96 and 0.74–0.84, respectively. However, the lowest and highest values of both similarity indices were broad, reflecting the musculoskeletal system’s redundancy within and between participants. Furthermore, the significant differences in the degree of variability between the trunk synergies may represent the different neural features of synergy organization and strategies to overcome the various mechanical demands of a motor task.https://doi.org/10.1038/s41598-023-28467-6 |
| spellingShingle | Hiroki Saito Hikaru Yokoyama Atsushi Sasaki Kazuya Matsushita Kimitaka Nakazawa Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals Scientific Reports |
| title | Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals |
| title_full | Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals |
| title_fullStr | Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals |
| title_full_unstemmed | Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals |
| title_short | Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals |
| title_sort | variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals |
| url | https://doi.org/10.1038/s41598-023-28467-6 |
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