An Algorithm for Choosing the Optimal Number of Muscle Synergies during Walking
In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algo...
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| Published in | Sensors (Basel, Switzerland) Vol. 21; no. 10; p. 3311 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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11.05.2021
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| Online Access | Get full text |
| ISSN | 1424-8220 1424-8220 |
| DOI | 10.3390/s21103311 |
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| Abstract | In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algorithm for choosing the optimal number of muscle synergies (ChoOSyn), which can overcome the limitations of VAF-based methods. The proposed algorithm is built considering the following principles: (1) muscle synergies should be highly consistent during the various motor task epochs (i.e., remaining stable in time), (2) muscle synergies should constitute a base with low intra-level similarity (i.e., to obtain information-rich synergies, avoiding redundancy). The algorithm performances were evaluated against traditional approaches (threshold-VAF at 90% and 95%, elbow-VAF and plateau-VAF), using both a simulated dataset and a real dataset of 20 subjects. The performance evaluation was carried out by analyzing muscle synergies extracted from surface electromyographic (sEMG) signals collected during walking tasks lasting 5 min. On the simulated dataset, ChoOSyn showed comparable performances compared to VAF-based methods, while, in the real dataset, it clearly outperformed the other methods, in terms of the fraction of correct classifications, mean error (ME), and root mean square error (RMSE). The proposed approach may be beneficial to standardize the selection of the number of muscle synergies between different research laboratories, independent of arbitrary thresholds. |
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| AbstractList | In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algorithm for choosing the optimal number of muscle synergies (ChoOSyn), which can overcome the limitations of VAF-based methods. The proposed algorithm is built considering the following principles: (1) muscle synergies should be highly consistent during the various motor task epochs (i.e., remaining stable in time), (2) muscle synergies should constitute a base with low intra-level similarity (i.e., to obtain information-rich synergies, avoiding redundancy). The algorithm performances were evaluated against traditional approaches (threshold-VAF at 90% and 95%, elbow-VAF and plateau-VAF), using both a simulated dataset and a real dataset of 20 subjects. The performance evaluation was carried out by analyzing muscle synergies extracted from surface electromyographic (sEMG) signals collected during walking tasks lasting 5 min. On the simulated dataset, ChoOSyn showed comparable performances compared to VAF-based methods, while, in the real dataset, it clearly outperformed the other methods, in terms of the fraction of correct classifications, mean error (ME), and root mean square error (RMSE). The proposed approach may be beneficial to standardize the selection of the number of muscle synergies between different research laboratories, independent of arbitrary thresholds. In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algorithm for choosing the optimal number of muscle synergies (ChoOSyn), which can overcome the limitations of VAF-based methods. The proposed algorithm is built considering the following principles: (1) muscle synergies should be highly consistent during the various motor task epochs (i.e., remaining stable in time), (2) muscle synergies should constitute a base with low intra-level similarity (i.e., to obtain information-rich synergies, avoiding redundancy). The algorithm performances were evaluated against traditional approaches (threshold-VAF at 90% and 95%, elbow-VAF and plateau-VAF), using both a simulated dataset and a real dataset of 20 subjects. The performance evaluation was carried out by analyzing muscle synergies extracted from surface electromyographic (sEMG) signals collected during walking tasks lasting 5 min. On the simulated dataset, ChoOSyn showed comparable performances compared to VAF-based methods, while, in the real dataset, it clearly outperformed the other methods, in terms of the fraction of correct classifications, mean error (ME), and root mean square error (RMSE). The proposed approach may be beneficial to standardize the selection of the number of muscle synergies between different research laboratories, independent of arbitrary thresholds.In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algorithm for choosing the optimal number of muscle synergies (ChoOSyn), which can overcome the limitations of VAF-based methods. The proposed algorithm is built considering the following principles: (1) muscle synergies should be highly consistent during the various motor task epochs (i.e., remaining stable in time), (2) muscle synergies should constitute a base with low intra-level similarity (i.e., to obtain information-rich synergies, avoiding redundancy). The algorithm performances were evaluated against traditional approaches (threshold-VAF at 90% and 95%, elbow-VAF and plateau-VAF), using both a simulated dataset and a real dataset of 20 subjects. The performance evaluation was carried out by analyzing muscle synergies extracted from surface electromyographic (sEMG) signals collected during walking tasks lasting 5 min. On the simulated dataset, ChoOSyn showed comparable performances compared to VAF-based methods, while, in the real dataset, it clearly outperformed the other methods, in terms of the fraction of correct classifications, mean error (ME), and root mean square error (RMSE). The proposed approach may be beneficial to standardize the selection of the number of muscle synergies between different research laboratories, independent of arbitrary thresholds. |
| Author | Ballarini, Riccardo Ghislieri, Marco Knaflitz, Marco Agostini, Valentina |
| AuthorAffiliation | 1 Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy; riccardo.ballarini@studenti.polito.it (R.B.); marco.ghislieri@polito.it (M.G.); marco.knaflitz@polito.it (M.K.) 2 PoliTo BIO Med Lab, Politecnico di Torino, 10129 Turin, Italy |
| AuthorAffiliation_xml | – name: 1 Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy; riccardo.ballarini@studenti.polito.it (R.B.); marco.ghislieri@polito.it (M.G.); marco.knaflitz@polito.it (M.K.) – name: 2 PoliTo BIO Med Lab, Politecnico di Torino, 10129 Turin, Italy |
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| Cites_doi | 10.3389/fnhum.2017.00586 10.1109/TBME.2011.2170687 10.1016/j.jelekin.2018.09.009 10.1152/jn.00758.2015 10.1016/j.apmr.2015.02.014 10.1016/j.clinbiomech.2015.07.010 10.3390/s20154297 10.1016/j.neures.2015.12.008 10.1016/j.isci.2019.04.008 10.1007/s10439-016-1660-0 10.3389/fneur.2020.00994 10.1073/pnas.0910114106 10.1152/jn.00222.2005 10.1152/jn.00825.2009 10.1137/07069239X 10.1073/pnas.0500199102 10.1109/METROI4.2019.8792842 10.3389/fnhum.2014.00335 10.1007/978-3-319-24901-8_10 10.1109/MeMeA.2019.8802229 10.3389/fncom.2013.00105 10.1109/TNSRE.2020.2965179 10.3389/fncom.2017.00078 10.1016/j.gaitpost.2013.01.020 10.1155/2018/3629347 10.1038/nn1010 10.3390/s20113209 10.1109/MeMeA.2018.8438602 10.1186/1743-0003-9-64 10.3390/s21051904 10.1016/j.jbiomech.2017.08.006 10.3389/fnhum.2016.00455 10.1523/JNEUROSCI.4904-04.2005 10.1016/j.jelekin.2017.01.002 10.1038/s41598-018-26780-z 10.1109/MeMeA.2018.8438760 10.1109/I2MTC.2017.7969722 10.1177/001316446002000104 10.3389/fncom.2013.00008 10.1109/TNSRE.2020.3030847 10.1016/j.clinph.2013.02.006 10.1109/LSC.2018.8572075 |
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| References | Oliveira (ref_37) 2014; 8 Bizzi (ref_39) 2005; 102 Barroso (ref_1) 2017; 63 Ghislieri (ref_35) 2020; 28 Sawers (ref_17) 2015; 114 Kim (ref_38) 2008; 30 Falaki (ref_6) 2017; 33 Ambrosini (ref_14) 2016; 44 ref_33 Torricelli (ref_36) 2016; Volume 10 Agostini (ref_45) 2015; 30 Ghislieri (ref_22) 2020; 28 Banks (ref_2) 2017; 11 Cohen (ref_41) 1960; 20 Delis (ref_29) 2013; 7 Agostini (ref_34) 2011; 59 Rodriguez (ref_19) 2013; 124 Taborri (ref_8) 2018; 2018 Clark (ref_13) 2010; 103 Lee (ref_12) 1999; 401 Tresch (ref_11) 2006; 95 Saltiel (ref_10) 2003; 6 Hirashima (ref_26) 2016; 104 ref_25 ref_24 Routson (ref_15) 2013; 38 ref_21 ref_20 ref_42 Steele (ref_18) 2013; 7 Yokoyama (ref_27) 2019; 15 Kim (ref_28) 2016; 10 ref_3 Cheung (ref_16) 2009; 106 Agostini (ref_31) 2020; 11 Agostini (ref_43) 2015; 96 Benedetti (ref_44) 2012; 9 Rimini (ref_23) 2017; 11 ref_9 Cheung (ref_40) 2005; 25 Delis (ref_30) 2018; 8 Feeney (ref_4) 2018; 43 ref_5 ref_7 Soomro (ref_32) 2018; 2018 |
| References_xml | – volume: 11 start-page: 586 year: 2017 ident: ref_23 article-title: Intra-Subject Consistency during Locomotion: Similarity in Shared and Subject-Specific Muscle Synergies publication-title: Front. Hum. Neurosci. doi: 10.3389/fnhum.2017.00586 – volume: 59 start-page: 219 year: 2011 ident: ref_34 article-title: An Algorithm for the Estimation of the Signal-To-Noise Ratio in Surface Myoelectric Signals Generated During Cyclic Movements publication-title: IEEE Trans. Biomed. Eng. doi: 10.1109/TBME.2011.2170687 – volume: 43 start-page: 95 year: 2018 ident: ref_4 article-title: Individuals with sacroiliac joint dysfunction display asymmetrical gait and a depressed synergy between muscles providing sacroiliac joint force closure when walking publication-title: J. Electromyogr. Kinesiol. doi: 10.1016/j.jelekin.2018.09.009 – volume: 114 start-page: 3359 year: 2015 ident: ref_17 article-title: Long-term training modifies the modular structure and organization of walking balance control publication-title: J. Neurophysiol. doi: 10.1152/jn.00758.2015 – volume: 96 start-page: 1235 year: 2015 ident: ref_43 article-title: Instrumented Gait Analysis for an Objective Pre-/Postassessment of Tap Test in Normal Pressure Hydrocephalus publication-title: Arch. Phys. Med. Rehabil. doi: 10.1016/j.apmr.2015.02.014 – volume: 30 start-page: 908 year: 2015 ident: ref_45 article-title: Multiple gait patterns within the same Winters class in children with hemiplegic cerebral palsy publication-title: Clin. Biomech. doi: 10.1016/j.clinbiomech.2015.07.010 – ident: ref_20 doi: 10.3390/s20154297 – volume: 104 start-page: 80 year: 2016 ident: ref_26 article-title: How does the brain solve muscle redundancy? Filling the gap between optimization and muscle synergy hypotheses publication-title: Neurosci. Res. doi: 10.1016/j.neures.2015.12.008 – volume: 15 start-page: 623 year: 2019 ident: ref_27 article-title: Cortical Correlates of Locomotor Muscle Synergy Activation in Humans: An Electroencephalographic Decoding Study publication-title: iScience doi: 10.1016/j.isci.2019.04.008 – volume: 44 start-page: 3238 year: 2016 ident: ref_14 article-title: Neuro-Mechanics of Recumbent Leg Cycling in Post-Acute Stroke Patients publication-title: Ann. Biomed. Eng. doi: 10.1007/s10439-016-1660-0 – volume: 11 start-page: 1 year: 2020 ident: ref_31 article-title: Surface Electromyography Applied to Gait Analysis: How to Improve Its Impact in Clinics? publication-title: Front. Neurol. doi: 10.3389/fneur.2020.00994 – volume: 106 start-page: 19563 year: 2009 ident: ref_16 article-title: Stability of muscle synergies for voluntary actions after cortical stroke in humans publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.0910114106 – volume: 95 start-page: 2199 year: 2006 ident: ref_11 article-title: Matrix Factorization Algorithms for the Identification of Muscle Synergies: Evaluation on Simulated and Experimental Data Sets publication-title: J. Neurophysiol. doi: 10.1152/jn.00222.2005 – volume: 103 start-page: 844 year: 2010 ident: ref_13 article-title: Merging of Healthy Motor Modules Predicts Reduced Locomotor Performance and Muscle Coordination Complexity Post-Stroke publication-title: J. Neurophysiol. doi: 10.1152/jn.00825.2009 – volume: 30 start-page: 713 year: 2008 ident: ref_38 article-title: Nonnegative Matrix Factorization Based on Alternating Nonnegativity Constrained Least Squares and Active Set Method publication-title: SIAM J. Matrix Anal. Appl. doi: 10.1137/07069239X – volume: 102 start-page: 3076 year: 2005 ident: ref_39 article-title: Shared and specific muscle synergies in natural motor behaviors publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.0500199102 – ident: ref_7 doi: 10.1109/METROI4.2019.8792842 – volume: 2018 start-page: 1 year: 2018 ident: ref_8 article-title: Feasibility of Muscle Synergy Outcomes in Clinics, Robotics, and Sports: A Systematic Review publication-title: Appl. Bionics Biomech. – volume: 8 start-page: 335 year: 2014 ident: ref_37 article-title: Motor modules of human locomotion: Influence of EMG averaging, concatenation, and number of step cycles publication-title: Front. Hum. Neurosci. doi: 10.3389/fnhum.2014.00335 – volume: Volume 10 start-page: 251 year: 2016 ident: ref_36 article-title: Muscle Synergies in Clinical Practice: Theoretical and Practical Implications publication-title: Emerging Therapies in Neurorehabilitation II doi: 10.1007/978-3-319-24901-8_10 – ident: ref_5 doi: 10.1109/MeMeA.2019.8802229 – volume: 7 start-page: 105 year: 2013 ident: ref_18 article-title: The number and choice of muscles impact the results of muscle synergy analyses publication-title: Front. Comput. Neurosci. doi: 10.3389/fncom.2013.00105 – volume: 28 start-page: 453 year: 2020 ident: ref_22 article-title: Muscle Synergies Extracted Using Principal Activations: Improvement of Robustness and Interpretability publication-title: IEEE Trans. Neural Syst. Rehabil. Eng. doi: 10.1109/TNSRE.2020.2965179 – ident: ref_25 – volume: 11 start-page: 1 year: 2017 ident: ref_2 article-title: Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke publication-title: Front. Comput. Neurosci. doi: 10.3389/fncom.2017.00078 – volume: 38 start-page: 511 year: 2013 ident: ref_15 article-title: The influence of locomotor rehabilitation on module quality and post-stroke hemiparetic walking performance publication-title: Gait Posture doi: 10.1016/j.gaitpost.2013.01.020 – volume: 2018 start-page: 1 year: 2018 ident: ref_32 article-title: Comparison of Initialization Techniques for the Accurate Extraction of Muscle Synergies from Myoelectric Signals via Nonnegative Matrix Factorization publication-title: Appl. Bionics Biomech. doi: 10.1155/2018/3629347 – volume: 6 start-page: 300 year: 2003 ident: ref_10 article-title: Combinations of muscle synergies in the construction of a natural motor behavior publication-title: Nat. Neurosci. doi: 10.1038/nn1010 – ident: ref_3 doi: 10.3390/s20113209 – ident: ref_33 doi: 10.1109/MeMeA.2018.8438602 – volume: 9 start-page: 64 year: 2012 ident: ref_44 article-title: Self-reported gait unsteadiness in mildly impaired neurological patients: An objective assessment through statistical gait analysis publication-title: J. Neuroeng. Rehabil. doi: 10.1186/1743-0003-9-64 – ident: ref_9 doi: 10.3390/s21051904 – volume: 63 start-page: 98 year: 2017 ident: ref_1 article-title: Combining muscle synergies and biomechanical analysis to assess gait in stroke patients publication-title: J. Biomech. doi: 10.1016/j.jbiomech.2017.08.006 – volume: 10 start-page: 455 year: 2016 ident: ref_28 article-title: Novel Methods to Enhance Precision and Reliability in Muscle Synergy Identification during Walking publication-title: Front. Hum. Neurosci. doi: 10.3389/fnhum.2016.00455 – volume: 25 start-page: 6419 year: 2005 ident: ref_40 article-title: Central and Sensory Contributions to the Activation and Organization of Muscle Synergies during Natural Motor Behaviors publication-title: J. Neurosci. doi: 10.1523/JNEUROSCI.4904-04.2005 – volume: 33 start-page: 20 year: 2017 ident: ref_6 article-title: Dopaminergic modulation of multi-muscle synergies in postural tasks performed by patients with Parkinson’s disease publication-title: J. Electromyogr. Kinesiol. doi: 10.1016/j.jelekin.2017.01.002 – volume: 8 start-page: 8391 year: 2018 ident: ref_30 article-title: Deciphering the functional role of spatial and temporal muscle synergies in whole-body movements publication-title: Sci. Rep. doi: 10.1038/s41598-018-26780-z – ident: ref_42 doi: 10.1109/MeMeA.2018.8438760 – ident: ref_24 doi: 10.1109/I2MTC.2017.7969722 – volume: 20 start-page: 37 year: 1960 ident: ref_41 article-title: A Coefficient of Agreement for Nominal Scales publication-title: Educ. Psychol. Meas. doi: 10.1177/001316446002000104 – volume: 401 start-page: 788 year: 1999 ident: ref_12 article-title: Learning the parts of objects by non-negative matrix factorization publication-title: Nat. Cell Biol. – volume: 7 start-page: 1 year: 2013 ident: ref_29 article-title: Quantitative evaluation of muscle synergy models: A single-trial task decoding approach publication-title: Front. Comput. Neurosci. doi: 10.3389/fncom.2013.00008 – volume: 28 start-page: 2914 year: 2020 ident: ref_35 article-title: Muscle Synergy Assessment During Single-Leg Stance publication-title: IEEE Trans. Neural Syst. Rehabil. Eng. doi: 10.1109/TNSRE.2020.3030847 – volume: 124 start-page: 1390 year: 2013 ident: ref_19 article-title: Persons with Parkinson’s disease exhibit decreased neuromuscular complexity during gait publication-title: Clin. Neurophysiol. doi: 10.1016/j.clinph.2013.02.006 – ident: ref_21 doi: 10.1109/LSC.2018.8572075 |
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| SubjectTerms | Algorithms Datasets Gait Hypotheses locomotion motor module Noise number of synergies Standard deviation VAF |
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| Title | An Algorithm for Choosing the Optimal Number of Muscle Synergies during Walking |
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