PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

A neuromechanical modeling of spinal cord injury locomotor system for simulating the rehabilitation effects

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Gait recovering after spinal cord injury (SCI) is a regular attempt in neurorehabilitation. For this purpose, various clinical techniques have been proposed until now. However, the feasibility of these techniques has not been theoretically investigated so much. This has been mainly for difficulties of gait modeling in SCI patients. Involving these problems, recently neuromechanical models of gait locomotion have been proposed for examining rehabilitation methods. However, these models were so simple that could not properly express rehabilitation effects. Notably, lesion intensity is a concern that was never attended in prior simulations. Due to this limitation, in this paper a new neuromechanical model is proposed that classifies patients based on intensity of trauma. Explicitly, the complete, severe and non-severe incomplete SCIs are imitated and effects of related clinical rehabi-litations are explored. Remarkably, the model indicates an incredible performance in explaining the rehabilitation effects through presenting the compliant results with clinical information. The suitability of this model is mainly for the applied neuromuscular plan that consists of a combined plan of central pattern generator (CPG) and neural reflexes that controls a double segment limb. The validity of this model is further proved by comparing the kinematic and kinetic results to the experimental data.
Twórcy
autor
  • Department of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran
  • Department of Mechanical Engineering, Tarbiat Modares University, Nasr Bridge, Jalal Al Ahmad Street, Tehran, Iran
  • Department of Physiology, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran
Bibliografia
  • [1] Dietz V. Body weight supported gait training: from laboratory to clinical setting. Brain Res Bull 2008;76:459–63.
  • [2] Grasso R, Ivanenko YP, Zago M, Molinari M, Scivoletto G, Castellano V, et al. Distributed plasticity of locomotor pattern generators in spinal cord injured patients. Brain 2004;127:16.
  • [3] Molinari M. Plasticity properties of CPG circuits in humans: impact on gait recovery. Brain Res Bull 2009;78:22–5.
  • [4] Knikou M. Neural control of locomotion and training-induced plasticity after spinal and cerebral lesions. Clin Neurophysiol 2010;121:1655–68.
  • [5] Fleerkotte BM, Koopman B, Buurke JH, Asseldon EHFv, van der Kooij H, Rietman JS. The effect of impedance-controlled robotic gait training on walking ability and quality in individuals with chronic incomplete spinal cord injury: an explorative study. J Neuroeng Rehabil 2014;11:15.
  • [6] Cai LL, Fong AJ, Otoshi CK, Liang Y, Burdick JW, Roy RR, et al. Implications of assist-as-needed robotic step training after a complete spinal cord injury on intrinsic strategies of motor learning. J Neurosci 2006;26:10564–8.
  • [7] Bien Z, Chung M-J, Chang P-H, Kwon D-S, Kim D-J, Han J-S, et al. Integration of a rehabilitation robotic system (KARES II) with human-friendly man-machine interaction units. Auton Robot 2004;16:27.
  • [8] Etlin A, Finkel E, Cherniak M, Lev-Tov A, Anglister L. The motor output of hindlimb innervating segments of the spinal cord is modulated by cholinergic activation of rostrally projecting sacral relay neurons. J Mol Neurosci 2014.
  • [9] Hillen BK, Abbas JJ, Jung R. Accelerating locomotor recovery after incomplete spinal injury. Ann NY Acad Sci 2013;1279:164–74.
  • [10] Hubli M, Dietz V. The physiological basis of neurorehabilitation-locomotor training after spinal cord injury. J Neuroeng Rehabil 2013;10:1–8.
  • [11] Zajac FE, Neptune RR, Kautz SA. Biomechanics and muscle coordination of human walking. Part II: Lessons from dynamical simulations and clinical implications. Gait Posture 2003;17:17.
  • [12] Komura T, Nagano A, Leung H, Shinagawa Y. Simulating pathological gait using the enhanced linear inverted pendulum model. IEEE Trans Biomed Eng 2004;52:12.
  • [13] Martínez F, Cifuentes C, Romero E. Simulation of normal and pathological gaits using a fusion knowledge strategy. J Neuroeng Rehabil 2013;10:12.
  • [14] Duysens J, Baken BC, Burgers L, Plat FM, den Otter AR, Kremer HP. Cutaneous reflexes from the foot during gait in hereditary spastic paraparesis. Clin Neurophysiol 2004;115:1057–62.
  • [15] McCreaa DA, Rybak IA. Organization of mammalian locomotor rhythm and pattern generation. Brain Res Rev 2008;57:134–46.
  • [16] Bellotti CPM, Jezernik S, Curt A. Development of a human neuro-musculo-skeletal model for investigation of spinal cord injury. Biol Cybern 2005;93:18.
  • [17] Jansen K, Groote FD, Aerts W, Schutter JD, Duysens J, Jonkers I. Altering length and velocity feedback during a neuro-musculoskeletal simulation of normal gait contributes to hemiparetic gait characteristics. J Neuroeng Rehabil 2014;11:15.
  • [18] Markin SN, Klishko AN, Shevtsova NA, Lemay MA, Prilutsky BI, Rybak IA. Afferent control of locomotor CPG: insights from a simple neuromechanical model. Ann NY Acad Sci 2010;1198:21–34.
  • [19] Spardy LE, Markin SN, Shevtsova NA, Prilutsky BI, Rybak IA, Rubin JE. A dynamical systems analysis of afferent control in a neuromechanical model of locomotion: I. Rhythm generation. J Neural Eng 2011;8.
  • [20] Rybak IA, Shevtsova NA, Lafreniere-Roula M, McCrea DA. Modelling spinal circuitry involved in locomotor pattern generation: insights from deletions during fictive locomotion. J Physiol 2006;577:617–39.
  • [21] Guertin PA. The mammalian central pattern generator for locomotion. Brain Res Rev 2009;62:45–56.
  • [22] Verdaasdonk BW, Koopman HF, Helm FC. Energy efficient and robust rhythmic limb movement by central pattern generators. Neural Netw 2006;19:388–400.
  • [23] Simoni MF. Sensory feedback in a half-center oscillator model. IEEE Trans Biomed Eng 2007;54:193–204.
  • [24] Williams CA, DeWeerth SP. Resonance tuning of a neuromechanical system with two negative sensory feedback configurations. Neurocomputing 2007;70:1954–9.
  • [25] Bliss TK, Iwasaki T, Bart-Smith H. Resonance entrainment of tensegrity structures via CPG control. Automatica 2012;48:2791–800.
  • [26] Guertin PA. Central pattern generator for locomotion: anatomical, physiological, and pathophysiological considerations. Front Neurol 2012;3:1–15.
  • [27] Daun-Gruhn S. A mathematical modeling study of inter-segmental coordination during stick insect walking. J Comput Neurosci 2011;30:255–78.
  • [28] Tamburella F, Scivoletto G, Molinari M. Somatosensory inputs by application of KinesioTaping: effects on spasticity, balance, and gait in chronic spinal cord injury. Front Hum Neurosci 2014;8:367.
  • [29] Jo S. Hierarchical neural control of human postural balance and bipedal walking in sagittal plane. Massachusetts Institute of Technology; 2006.
  • [30] Degallier S, Righetti L, Gay S, Ijspeert A. Toward simple control for complex, autonomous robotic applications: combining discrete and rhythmic motor primitives. Auton Robot 2011;31:155–81.
  • [31] Geyer H, Seyfarth A, Blickhan R. Positive force feedback in bouncing gaits. Proc Biol Sci 2003;270:2173–83.
  • [32] Geyer H, Herr H. A muscle-reflex model that encodes principles of legged mechanics produces human walking dynamics and muscle activities. IEEE Trans Neural Syst Rehabil Eng 2010;18:263–73.
  • [33] Pinnington HC, Lloyd DG, Besier TF, Dawson B. Kinematic and electromyography analysis of submaximal differences running on a firm surface compared with soft, dry sand. Eur J Appl Physiol 2005;94:242–53.
  • [34] Beres-Jones JA, Harkema SJ. The human spinal cord interprets velocity-dependent afferent input during stepping. Brain 2004;127:2232–46.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-24ccf466-b83c-4208-bb9b-471c3a9d0b30
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.