Modules of muscle recruitment can be extracted from electromyography (EMG) during motions, such as walking, running, and swimming, to identify key features of muscle coordination. These features may provide insight into gait adaptation as a result of powered assistance. The aim of this study was to investigate the changes (module size, module timing and weighting patterns) of surface EMG data during assisted and unassisted walking in an powered, myoelectric, ankle-foot orthosis (ankle exoskeleton).
Eight healthy subjects wore bilateral ankle exoskeletons and walked at 1.2 m/s on a treadmill. In three training sessions, subjects walked for 40 min in two conditions: unpowered (10 min) and powered (30 min). During each session, we extracted modules of muscle recruitment via nonnegative matrix factorization (NNMF) from the surface EMG signals of ten muscles in the lower limb. We evaluated reconstruction quality for each muscle individually using R2 and normalized root mean squared error (NRMSE). We hypothesized that the number of modules needed to reconstruct muscle data would be the same between conditions and that there would be greater similarity in module timings than weightings.
Across subjects, we found that six modules were sufficient to reconstruct the muscle data for both conditions, suggesting that the number of modules was preserved. The similarity of module timings and weightings between conditions was greater then random chance, indicating that muscle coordination was also preserved. Motor adaptation during walking in the exoskeleton was dominated by changes in the module timings rather than module weightings. The segment number and the session number were significant fixed effects in a linear mixed-effect model for the increase in R2 with time.
Our results show that subjects walking in a exoskeleton preserved the number of modules and the coordination of muscles within the modules across conditions. Training (motor adaptation within the session and motor skill consolidation across sessions) led to improved consistency of the muscle patterns. Subjects adapted primarily by changing the timing of their muscle patterns rather than the weightings of muscles in the modules. The results of this study give new insight into strategies for muscle recruitment during adaptation to a powered ankle exoskeleton.
Wolpert DM, Ghahramani Z, Flanagan JR. Perspectives and problems in motor learning. Trends Cogn Sci. 2001; 5(11):487–94. doi: 10.1016/S1364-6613(00)01773-3. Accessed 13 Dec 2014. CrossRefPubMed
Lacquaniti F, Ivanenko YP, Zago M. Patterned control of human locomotion. J Physiol. 2012; 590(10):2189–199. doi: 10.1113/jphysiol.2011.215137. Accessed 15 Aug 2014. CrossRefPubMedPubMedCentral
Alessandro C, Delis I, Nori F, Panzeri S, Berret B. Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives. Front Comput Neurosci. 2013; 7:43. doi: 10.3389/fncom.2013.00043. Accessed 12 Aug 2014. CrossRefPubMedPubMedCentral
Tresch MC, Jarc A. The case for and against muscle synergies. Curr Opin Neurobiol. 2009; 19(6):601–7. doi: 10.1016/j.conb.2009.09.002. Accessed 3 Apr 2013. CrossRefPubMedPubMedCentral
Ting L, Chiel H, Trumbower R, Allen J, McKay JL, Hackney M, Kesar T. Neuromechanical Principles Underlying Movement Modularity and Their Implications for Rehabilitation. Neuron. 2015; 86(1):38–54. doi: 10.1016/j.neuron.2015.02.042. Accessed 25 Jan 2016. CrossRefPubMedPubMedCentral
Reinkensmeyer DJ, Emken JL, Cramer SC. Robotics, Motor Learning, and Neurologic Recovery. Annu Rev Biomed Eng. 2004; 6(1):497–525. doi: 10.1146/annurev.bioeng.6.040803.140223. Accessed 26 Nov 2012. CrossRefPubMed
del-Ama AJ, Cuesta A, Rajasekaran V, Trincado F, In H, Reinkensmeyer D. Robotic Answered by Emerging Researchers In: Pons JL, Torricelli D, editors. Emerging Therapies in Neurorehabilitation. Biosystems & Biorobotics. Heidelberg: Springer Berlin;2014. p. 189–205.
Ivanenko YP, Cappellini G, Dominici N, Poppele RE, Lacquaniti F. Coordination of Locomotion with Voluntary Movements in Humans. J Neurosci. 2005; 25(31):7238–253. doi: 10.1523/JNEUROSCI.1327-05.2005. Accessed 9 June 2015. CrossRefPubMed
Oliveira AS, Silva PB, Lund ME, Kersting UG, Farina D. Fast changes in direction during human locomotion are executed by impulsive activation of motor modules. Neuroscience. 2013; 228:283–93. doi: 10.1016/j.neuroscience.2012.10.027. Accessed 9 June 2015. CrossRefPubMed
Barroso FO, Torricelli D, Moreno JC, Taylor J, Gomez-Soriano J, Bravo-Esteban E, Piazza S, Santos C, Pons JL. Shared muscle synergies in human walking and cycling. J Neurophys. 2014:00220–2014. doi: 10.1152/jn.00220.2014. Accessed 23 Oct 2014.
Chvatal SAPD, Ting LHPD. Common muscle synergies for balance and walking. Front Comput Neurosci. 2013; 7:48. doi: 10.3389/fncom.2013.00048. Accessed 12 Aug 2014. CrossRefPubMedPubMedCentral
Ivanenko YP, Poppele RE, Lacquaniti F. Five basic muscle activation patterns account for muscle activity during human locomotion. J Physiol. 2004; 556(1):267–82. doi: 10.1113/jphysiol.2003.057174. Accessed 16 June 2015. CrossRefPubMedPubMedCentral
Oliveira AS, Gizzi L, Farina D, Kersting UG. Motor modules of human locomotion: influence of EMG averaging, concatenation, and number of step cycles. Front Hum Neurosci. 2014;8. doi: 10.3389/fnhum.2014.00335. Accessed 15 Aug 2014.
Gonzalez-Vargas J, Sartori M, Dosen S, Torricelli D, Pons JL, Farina D. A predictive model of muscle excitations based on muscle modularity for a large repertoire of human locomotion conditions. Front Comput Neurosci. 2015; 114. doi: 10.3389/fncom.2015.00114. Accessed 20 July 2016.
Coscia M, Cheung VC, Tropea P, Koenig A, Monaco V, Bennis C, Micera S, Bonato P. The effect of arm weight support on upper limb muscle synergies during reaching movements. J neuroengineering and Rehabil. 2014; 11(1):22. CrossRef
Jiang N, Rehbaum H, Vujaklija I, Graimann B, Farina D. Intuitive, Online, Simultaneous, and Proportional Myoelectric Control Over Two Degrees-of-Freedom in Upper Limb Amputees. IEEE Trans Neural Syst Rehabil Eng. 2014; 22(3):501–10. doi: 10.1109/TNSRE.2013.2278411. Accessed 9 Mar 2017. CrossRefPubMed
Gentner R, Edmunds T, Pai DK, d’Avella A. Robustness of muscle synergies during visuomotor adaptation. Front Comput Neurosci. 2013;7. doi: 10.3389/fncom.2013.00120. Accessed 26 Apr 2017.
Berger DJ, Gentner R, Edmunds T, Pai DK, d’Avella A. Differences in Adaptation Rates after Virtual Surgeries Provide Direct Evidence for Modularity. J Neurosci. 2013; 33(30):12384–94. doi: 10.1523/JNEUROSCI.0122-13.2013. Accessed 24 Apr 2017. CrossRefPubMed
Sylos-Labini F, La Scaleia V, d’Avella A, Pisotta I, Tamburella F, Scivoletto G, Molinari M, Wang S, Wang L, van Asseldonk E, van der Kooij H, Hoellinger T, Cheron G, Thorsteinsson F, Ilzkovitz M, Gancet J, Hauffe R, Zanov F, Lacquaniti F, Ivanenko YP. EMG patterns during assisted walking in the exoskeleton. Front Hum Neurosci. 2014; 8:423. doi: 10.3389/fnhum.2014.00423. CrossRefPubMedPubMedCentral
Collins SH, Wiggin MB, Sawicki GS. Reducing the energy cost of human walking using an unpowered exoskeleton. Nature advance online publication. 2015. doi: 10.1038/nature14288. Accessed 7 Apr 2015.
Steele KM, Jackson RW, Shuman BR, Collins SH. Muscle recruitment and coordination with an ankle exoskeleton. J Biomech. 2017; 59:50–8. doi: 10.1016/j.jbiomech.2017.05.010. Accessed 17 July 2017. CrossRefPubMed
Chvatal SA, Ting LH. Voluntary and Reactive Recruitment of Locomotor Muscle Synergies during Perturbed Walking. J Neurosci. 2012; 32(35):12237–50. doi: 10.1523/JNEUROSCI.6344-11.2012. Accessed 14 Aug 2014. CrossRefPubMedPubMedCentral
Koller JR, Jacobs DA, Ferris DP, Remy CD. Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton. J NeuroEngineering Rehabil. 2015; 12(1):97. doi: 10.1186/s12984-015-0086-5. Accessed 12 Nov 2015. CrossRef
Gordon KE, Ferris DP. Learning to walk with a robotic ankle exoskeleton. Journal of Biomechanics. 2007; 40(12):2636–644. doi: 10.1016/j.jbiomech.2006.12.006. Accessed 31 Oct 2012. CrossRefPubMed
Shadmehr R, Holcomb HH. Neural Correlates of Motor Memory Consolidation. Science. 1997; 277(5327):821–5. doi: 10.1126/science.277.5327.821. Accessed 9 Apr 2017. CrossRefPubMed
Hermens HJ, Freriks B, Disselhorst-Klug C, Rau G. Development of recommendations for SEMG sensors and sensor placement procedures. J Electromyogr Kinesiol. 2000; 10(5):361–74. doi: 10.1016/S1050-6411(00)00027-4. Accessed 2 Jan 2016. CrossRefPubMed
Davis BL, Vaughan CL. Phasic behavior of EMG signals during gait: Use of multivariate statistics. J Electromyogr Kinesiol. 1993; 3(1):51–60. doi: 10.1016/1050-6411(93)90023-P. Accessed 31 Jan 2016. CrossRefPubMed
Wang Y, Asaka T, Zatsiorsky VM, Latash ML. Muscle synergies during voluntary body sway: combining across-trials and within-a-trial analyses. Exp Brain Res. 2006; 174(4):679–93. doi: 10.1007/s00221-006-0513-8. Accessed 12 Aug 2014. CrossRefPubMed
d’Avella A, Tresch MC. Modularity in the motor system: decomposition of muscle patterns as combinations of time-varying synergies. Adv Neural Inf Process Syst. 2002; 1:141–8.
Berry MW, Browne M, Langville AN, Pauca VP, Plemmons RJ. Algorithms and applications for approximate nonnegative matrix factorization. Comput Stat Data Anal. 2007; 52(1):155–73. doi: 10.1016/j.csda.2006.11.006. Accessed 1 Jan 2016. CrossRef
Burkholder TJ, Antwerp KW. Practical limits on muscle synergy identification by non-negative matrix factorization in systems with mechanical constraints. Med Biol Eng Comput. 2013; 51(1-2):187–96. doi: 10.1007/s11517-012-0983-8. Accessed 15 Aug 2014. CrossRefPubMed
Sartori M, Gizzi L, Lloyd DG, Farina D. A musculoskeletal model of human locomotion driven by a low dimensional set of impulsive excitation primitives. Front Comput Neurosci. 2013;7. doi: 10.3389/fncom.2013.00079. Accessed 15 Aug 2014.
Overduin S, d’Avella A, Carmena J, Bizzi E. Microstimulation Activates a Handful of Muscle Synergies. Neuron. 2012; 76(6):1071–7. doi: 10.1016/j.neuron.2012.10.018. Accessed 15 Aug 2014. CrossRefPubMedPubMedCentral
Ajiboye AB, Weir RF. Muscle synergies as a predictive framework for the EMG patterns of new hand postures. J Neural Eng. 2009; 6(3):036004. doi: 10.1088/1741-2560/6/3/036004. Accessed 19 Apr 2017. CrossRefPubMedPubMedCentral
Steele KM, Tresch MC, Perreault EJ. The number and choice of muscles impact the results of muscle synergy analyses. Front Comput Neurosci. 2013;7. doi: 10.3389/fncom.2013.00105. Accessed 10 Aug 2014.
De Groote F, Jonkers I, Duysens J. Task constraints and minimization of muscle effort result in a small number of muscle synergies during gait. Front Comput Neurosci. 2014; 8:115. doi: 10.3389/fncom.2014.00115. Accessed 22 Oct 2014. CrossRefPubMedPubMedCentral
Oliveira AS, Gizzi L, Ketabi S, Farina D, Kersting UG. Modular Control of Treadmill vs Overground Running. PLOS ONE. 2016; 11(4):0153307. doi: 10.1371/journal.pone.0153307. Accessed 15 May 2016. CrossRef
Rose S, Spinks N, Canhoto AI. Management Research: Applying the Principles. Abingdon: Routledge; 2014.
George D, Mallery P. IBM SPSS Statistics 23 Step by Step: A Simple Guide and Reference. Abingdon: Routledge; 2016.
Turpin NA, Guével A, Durand S, Hug F. No evidence of expertise-related changes in muscle synergies during rowing. J Electromyogr Kinesiol. 2011; 21(6):1030–40. doi: 10.1016/j.jelekin.2011.07.013. Accessed 22 June 2016. CrossRefPubMed
Frère J, Hug F. Between-subject variability of muscle synergies during a complex motor skill. Front Comput Neurosci. 2012;6. doi: 10.3389/fncom.2012.00099. Accessed 9 Feb 2015.
Santello M, Lang CE. Are movement disorders and sensorimotor injuries pathologic synergies? When normal multi-joint movement synergies become pathologic. Front Hum Neurosci. 2015; 8:1050. doi: 10.3389/fnhum.2014.01050. Accessed 2 Oct 2016. CrossRefPubMedPubMedCentral
Rugy Ad, Loeb GE, Carroll TJ. Muscle Coordination Is Habitual Rather than Optimal. J Neurosci. 2012; 32(21):7384–391. doi: 10.1523/JNEUROSCI.5792-11.2012. Accessed 17 June 2015. CrossRefPubMed
de Rugy A, Loeb G, Carroll T. Are muscle synergies useful for neural control?Front Comput Neurosci. 2013; 7:19. doi: 10.3389/fncom.2013.00019. Accessed 12 Aug 2014. CrossRefPubMedPubMedCentral
Sohn MH, Ting LH. Suboptimal Muscle Synergy Activation Patterns Generalize their Motor Function across Postures. Front Comput Neurosci. 2016;7. doi: 10.3389/fncom.2016.00007. Accessed 29 June 2016.
Loeb GE. Optimal isn’t good enough. Biol Cybern. 2012; 106(11-12):757–65. doi: 10.1007/s00422-012-0514-6. Accessed 26 June 2016. CrossRefPubMed
- Motor modules during adaptation to walking in a powered ankle exoskeleton
Daniel A. Jacobs
Jeffrey R. Koller
Katherine M. Steele
Daniel P. Ferris
- BioMed Central