Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke
Muscle synergy analysis (MSA) is a mathematical technique that reduces the dimensionality of electromyographic (EMG) data. Used increasingly in biomechanics research, MSA requires methodological choices at each stage of the analysis. Differences in methodological steps affect the overall outcome, ma...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2017-08-01
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| Series: | Frontiers in Computational Neuroscience |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fncom.2017.00078/full |
| _version_ | 1818005588421902336 |
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| author | Caitlin L. Banks Caitlin L. Banks Caitlin L. Banks Mihir M. Pai Theresa E. McGuirk Benjamin J. Fregly Benjamin J. Fregly Carolynn Patten Carolynn Patten |
| author_facet | Caitlin L. Banks Caitlin L. Banks Caitlin L. Banks Mihir M. Pai Theresa E. McGuirk Benjamin J. Fregly Benjamin J. Fregly Carolynn Patten Carolynn Patten |
| author_sort | Caitlin L. Banks |
| collection | DOAJ |
| description | Muscle synergy analysis (MSA) is a mathematical technique that reduces the dimensionality of electromyographic (EMG) data. Used increasingly in biomechanics research, MSA requires methodological choices at each stage of the analysis. Differences in methodological steps affect the overall outcome, making it difficult to compare results across studies. We applied MSA to EMG data collected from individuals post-stroke identified as either responders (RES) or non-responders (nRES) on the basis of a critical post-treatment increase in walking speed. Importantly, no clinical or functional indicators identified differences between the cohort of RES and nRES at baseline. For this exploratory study, we selected the five highest RES and five lowest nRES available from a larger sample. Our goal was to assess how the methodological choices made before, during, and after MSA affect the ability to differentiate two groups with intrinsic physiologic differences based on MSA results. We investigated 30 variations in MSA methodology to determine which choices allowed differentiation of RES from nRES at baseline. Trial-to-trial variability in time-independent synergy vectors (SVs) and time-varying neural commands (NCs) were measured as a function of: (1) number of synergies computed; (2) EMG normalization method before MSA; (3) whether SVs were held constant across trials or allowed to vary during MSA; and (4) synergy analysis output normalization method after MSA. MSA methodology had a strong effect on our ability to differentiate RES from nRES at baseline. Across all 10 individuals and MSA variations, two synergies were needed to reach an average of 90% variance accounted for (VAF). Based on effect sizes, differences in SV and NC variability between groups were greatest using two synergies with SVs that varied from trial-to-trial. Differences in SV variability were clearest using unit magnitude per trial EMG normalization, while NC variability was less sensitive to EMG normalization method. No outcomes were greatly impacted by output normalization method. MSA variability for some, but not all, methods successfully differentiated intrinsic physiological differences inaccessible to traditional clinical or biomechanical assessments. Our results were sensitive to methodological choices, highlighting the need for disclosure of all aspects of MSA methodology in future studies. |
| first_indexed | 2024-04-14T04:46:07Z |
| format | Article |
| id | doaj.art-064f4ce1d99d4cff908c089e3bc6670e |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-04-14T04:46:07Z |
| publishDate | 2017-08-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-064f4ce1d99d4cff908c089e3bc6670e2022-12-22T02:11:27ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882017-08-011110.3389/fncom.2017.00078257008Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following StrokeCaitlin L. Banks0Caitlin L. Banks1Caitlin L. Banks2Mihir M. Pai3Theresa E. McGuirk4Benjamin J. Fregly5Benjamin J. Fregly6Carolynn Patten7Carolynn Patten8Neural Control of Movement Lab, Malcom Randall VA Medical CenterGainesville, FL, United StatesDepartment of Biomedical Engineering, University of FloridaGainesville, FL, United StatesRehabilitation Science Doctoral Program, Department of Physical Therapy, University of FloridaGainesville, FL, United StatesDepartment of Mechanical and Aerospace Engineering, University of FloridaGainesville, FL, United StatesNeural Control of Movement Lab, Malcom Randall VA Medical CenterGainesville, FL, United StatesDepartment of Biomedical Engineering, University of FloridaGainesville, FL, United StatesDepartment of Mechanical and Aerospace Engineering, University of FloridaGainesville, FL, United StatesNeural Control of Movement Lab, Malcom Randall VA Medical CenterGainesville, FL, United StatesRehabilitation Science Doctoral Program, Department of Physical Therapy, University of FloridaGainesville, FL, United StatesMuscle synergy analysis (MSA) is a mathematical technique that reduces the dimensionality of electromyographic (EMG) data. Used increasingly in biomechanics research, MSA requires methodological choices at each stage of the analysis. Differences in methodological steps affect the overall outcome, making it difficult to compare results across studies. We applied MSA to EMG data collected from individuals post-stroke identified as either responders (RES) or non-responders (nRES) on the basis of a critical post-treatment increase in walking speed. Importantly, no clinical or functional indicators identified differences between the cohort of RES and nRES at baseline. For this exploratory study, we selected the five highest RES and five lowest nRES available from a larger sample. Our goal was to assess how the methodological choices made before, during, and after MSA affect the ability to differentiate two groups with intrinsic physiologic differences based on MSA results. We investigated 30 variations in MSA methodology to determine which choices allowed differentiation of RES from nRES at baseline. Trial-to-trial variability in time-independent synergy vectors (SVs) and time-varying neural commands (NCs) were measured as a function of: (1) number of synergies computed; (2) EMG normalization method before MSA; (3) whether SVs were held constant across trials or allowed to vary during MSA; and (4) synergy analysis output normalization method after MSA. MSA methodology had a strong effect on our ability to differentiate RES from nRES at baseline. Across all 10 individuals and MSA variations, two synergies were needed to reach an average of 90% variance accounted for (VAF). Based on effect sizes, differences in SV and NC variability between groups were greatest using two synergies with SVs that varied from trial-to-trial. Differences in SV variability were clearest using unit magnitude per trial EMG normalization, while NC variability was less sensitive to EMG normalization method. No outcomes were greatly impacted by output normalization method. MSA variability for some, but not all, methods successfully differentiated intrinsic physiological differences inaccessible to traditional clinical or biomechanical assessments. Our results were sensitive to methodological choices, highlighting the need for disclosure of all aspects of MSA methodology in future studies.http://journal.frontiersin.org/article/10.3389/fncom.2017.00078/fullmuscle synergiesmotor modulesstrokelocomotionEMGvariability |
| spellingShingle | Caitlin L. Banks Caitlin L. Banks Caitlin L. Banks Mihir M. Pai Theresa E. McGuirk Benjamin J. Fregly Benjamin J. Fregly Carolynn Patten Carolynn Patten Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke Frontiers in Computational Neuroscience muscle synergies motor modules stroke locomotion EMG variability |
| title | Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke |
| title_full | Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke |
| title_fullStr | Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke |
| title_full_unstemmed | Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke |
| title_short | Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke |
| title_sort | methodological choices in muscle synergy analysis impact differentiation of physiological characteristics following stroke |
| topic | muscle synergies motor modules stroke locomotion EMG variability |
| url | http://journal.frontiersin.org/article/10.3389/fncom.2017.00078/full |
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