Muscle coordination analysis by time-varying muscle synergy extraction during cycling across various mechanical conditions

• Autorzy: Esmaeili Javad , Maleki Ali

Identyfikatory

DOI

10.1016/j.bbe.2019.10.005

• Języki publikacji: EN

Abstrakty

EN

Central nervous system (CNS) uses the combination of a small number of motor primitives, named muscle synergies, for simplification of motor control in human movement. The aim of this study was to investigate the muscle coordination in both leg muscles during pedaling by time-varying muscle synergy extraction. Twenty healthy subjects performed three 6-min cycling tasks over a range of rotational speed (40, 50, and 60 rpm) and resistant torque (3, 5, and 7 N/M). Surface electromyography signals were recorded during pedaling from eight muscles of the right and left lower limbs. We extracted four time-varying muscle synergies from sEMG patterns. Mean and standard deviation of the quality of the signal reconstruction (R²) for all subjects was obtained 0.9328 ± 0.0120. We investigated the similarity of muscle synergies during cycling across various mechanical conditions. We found the high degrees of similarity (>0.85) among the sets of time-varying muscle synergies across mechanical conditions and also across subjects. Our results show that the same motor control strategies for cycling are used by all subjects in various mechanical conditions.

Słowa kluczowe

EN

time varying muscle synergy; pedaling; surface electromyography; motor control

PL

synergia mięśniowa; pedałowanie; elektromiografia powierzchniowa; kontrola motoryki

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2020
• Tom: Vol. 40, no. 1
• Strony: 90--99
• Opis fizyczny: Bibliogr. 38 poz., rys., tab., wykr.

Twórcy

autor

Esmaeili Javad

• Electrical and Computer Engineering Faculty, Semnan University, Semnan, Iran

autor

Maleki Ali

• Biomedical Engineering Department, Semnan University, Semnan, Iran

Bibliografia

• [1] Bernstein NA. The co-ordination and regulation of movements. London: Pergamon Press; 1967.
• [2] Latash ML, Gorniak S, Zatsiorsky VM. Hierarchies of synergies in human movements. Kinesiol 2008;40:29–38.
• [3] d'Avella A, Giese M, Ivanenko YP, Schack T, Flash T. Editorial. Modularity in motor control: from muscle synergies to cognitive action representation. Front Comput Neurosci 2015;9(126).
• [4] Latash ML. Stages in learning motor synergies: a view based on the equilibrium-point hypothesis. Hum Mov Sci 2010;29 (5):642–54.
• [5] Costa-Garc¨ia A, Itkonen M, Yamasaki H, Shibata-Alnajjar F, Shimoda SA. Novel approach to the segmentation of sEMG data based on the activation and deactivation of muscle synergies during movement. IEEE Robot Autom Lett 2018;3 (3):1972–7.
• [6] Yang N, An Q, Yamakawa H, Tamura Y, Yamashita A, Asama H. Clarification of muscle synergy structure during standing-up motion of healthy young, elderly and post-stroke patients. In: IEEE international conference on rehabilitation robotics (ICORR), London; 2017.
• [7] An Q, Yamakawa H, Yamashita A, Asama H. Different temporal structure of muscle synergy between sit-to-Walk and sit-to-Stand motions in human standing leg. Converging clinical and engineering research on neurorehabilitation II. Biosys Biorobot 2017;15:933–7.
• [8] Chvatal SA, Ting LH. Common muscle synergies for balance and walking. Front Comput Neurosci 2013;7(48).
• [9] Matsunaga N, Imai A, Kaneoka K. Comparison of muscle synergies before and after 10 minutes of running. J Phys Ther Sci 2017;29(7):1242–6.
• [10] Nishida K, Hagio S, Kibushi B, Moritani T, Kouzaki M. Comparison of muscle synergies for running between different foot strike patterns. PLoS One 2017;12(2).
• [11] d'Avella A, Lacquaniti F. Control of reaching movements by muscle synergy combinations. Front Comput Neurosci 2013;7(42).
• [12] Scano A, Chiavenna A, Malosio M, Molinari Tosatti L, Molteni F. Muscle synergies-based characterization and clustering of poststroke patients in reaching movements. Front Bioeng Biotechno 2017;5(62).
• [13] D'Andola M, Cesqui B, Fernandez L, D'Avella A. Spatiotemporal characteristics of muscle patterns for ball catching. Front Comput Neurosci 2013;7(107).
• [14] Saito A, Tomita A, Ando R, Watanabe K, Akima H. Similarity of muscle synergies extracted from the lower limb including the deep muscles between level and uphill treadmill walking. Gait Posture 2018;59:134–9.
• [15] Kibushi B, Hagio S, Moritani T, Kouzaki M. Speed-dependent modulation of muscle activity based on muscle synergies during treadmill walking. Front Hum Neurosci 2018;12:4.
• [16] De Marchis C, Castronovo AM, Bibbo D, Schmid M, Conforto S. Muscle synergies are consistent when pedaling under different biomechanical demands. In: 34th annual international conference of the IEEE engineering in medicine and biology society (EMBS), San Diego, California; 2012.
• [17] Saito A, Watanabe K, Akima H. Coordination among thigh muscles including the vastus intermedius and adductor magnus at different cycling intensities. Hum Mov Sci 2015;40:14–23.
• [18] Hug F, Turpin NA, Guével A, Dorel S. Is interindividual variability of EMG patterns in trained cyclists related to different muscle synergies? J Appl Physiol 2010;108:1727–36.
• [19] Turpin NA, Costes A, Moretto P, Watier B. Can muscle coordination explain the advantage of using the standing position during intense cycling? J Sci Med Sport 2017;20 (6):611–6.
• [20] De Marchis C, Schmid M, Bibbo D, Bernabucci I, Conforto S. Inter-individual variability of forces and modular muscle coordination in cycling: a study on untrained subjects. Hum Mov Sci 2013;32(6):1480–94.
• [21] Hug F, Dorel S. Electromyographic analysis of pedaling: a review. J Electromyogr Kinesiol 2009;19(2):182–98.
• [22] Tang L, Li F, Cao S, Zhang X, Wu D, Chen X. Muscle synergy analysis in children with cerebral palsy. J Neural Eng 2015;12(4).
• [23] Hug F. Can muscle coordination be precisely studied by surface electromyography? J Electromyogr Kinesiol 2011;21 (1):1–12.
• [24] Blake OM, Champoux Y, Wakeling JM. Muscle coordination patterns for efficient cycling. Med Sci Sports Exerc 2012;44 (5):926–38.
• [25] An Q, Ikemoto Y, Asama H. Muscle synergy analysis between young and elderly people in standing-up motion. J Robot Mechatro 2013;25(6):1038–49.
• [26] d'Avella A, Bizzi E. Shared and specific muscle synergies in natural motor behaviors. Proc Natl Acad Sci USA 2005;102 (8):3076–81.
• [27] Mallat SG, Zhang Z. Matching pursuits with time-frequency dictionaries. IEEE Trans Signal Process 1993;41(12):3397–415.
• [28] Barroso FO, Torricelli D, Bravo-Esteban E, Taylor J, Gómez- Soriano J, Santos C, et al. Muscle synergies in cycling after incomplete spinal cord injury: correlation with clinical measures of motor function and spasticity. Front Hum Neurosci 2015;9(706).
• [29] de Rugy A, Loeb GE, Carroll TJ. Are muscle synergies useful for neural control? Front Comput Neurosci 2013;7(19).
• [30] Steele KM, Tresch MC, Perreault EJ. The number and choice of muscles impact the results of muscle synergy analyses. Front Comput Neurosci 2013;7(105).
• [31] d'Avella A, Portone A, Lacquaniti F. Superposition and modulation of muscle synergies for reaching in response to a change in target location. J Neurophysiol 2011;106 (6):2796–812.
• [32] Quandt F, Hummel FC. The influence of functional electrical stimulation on hand motor recovery in stroke patients: a review. Exp Transl Stroke Med 2014;6(9).
• [33] Ison M, Artemiadis P. Proportional myoelectric control of robots: muscle synergy development drives performance enhancement, retainment, and generalization. IEEE Trans Robot 2015;31(2):259–68.
• [34] Hug F, Turpin NA, Couturier A, Dorel S. Consistency of muscle synergies during pedaling across different mechanical constraints. J Neurophysiol 2011;106:91–103.
• [35] De Marchis C, Severini G, Castronovo AM, Schmid M, Conforto S. Intermuscular coherence contributions in synergistic muscles during pedaling. Exp Brain Res 2015;233 (6):1907–19.
• [36] 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).
• [37] d'Avella A, Portone A, Fernandez L, Lacquaniti F. Control of fast-reaching movements by muscle synergy combinations. J Neurosci 2006;26(30):7791–810.
• [38] Overduin SA, d'Avella A, Roh J, Bizzi E. Modulation of muscle synergy recruitment in primate grasping. J Neurosci 2008;28(4):880–92.

Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).