Open Access Research

Effects of robotic guidance on the coordination of locomotion

Juan C Moreno1*, Filipe Barroso12, Dario Farina3, Leonardo Gizzi45, Cristina Santos2, Marco Molinari6 and José L Pons1

Author Affiliations

1 Bioengineering Group, Spanish National Research Council, CSIC, Carretera Campo Real, Madrid, Spain

2 ASBG (Adaptive Systems Behaviour Group), Department of Industrial Electronics, University of Minho, Azurém, Guimarães, Portugal

3 Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology Göttingen, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen, Georg-August University, Göttingen, Germany

4 Pain Clinic -Center for Anesthesiology, Emergency and Intensive Care Medicine, University Medical Center Göttingen, Georg-August University, Göttingen, Germany

5 Department of Movement and Sport Sciences, University of Rome “Foro Italico”, Rome, Italy

6 Fondazione S. Lucia, Roma, Italy

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Journal of NeuroEngineering and Rehabilitation 2013, 10:79  doi:10.1186/1743-0003-10-79

Published: 19 July 2013



Functional integration of motor activity patterns enables the production of coordinated movements, such as walking. The activation of muscles by weightened summation of activation signals has been demonstrated to represent the spatiotemporal components that determine motor behavior during walking. Exoskeleton robotic devices are now often used in the rehabilitation practice to assist physical therapy of individuals with neurological disorders. These devices are used to promote motor recovery by providing guidance force to the patients. The guidance should in principle lead to a muscle coordination similar to physiological human walking. However, the influence of robotic devices on locomotor patterns needs still to be characterized. The aim of this study was to analyze the effect of force guidance and gait speed on the modular organization of walking in a group of eight healthy subjects.


A group of healthy subjects walked on a treadmill with and without robotic aiding at speeds of 1.5, 2.0 and 2.5 Km/h. The guidance force was varied between 20%, 40%, 70% and 100% level of assistance. EMG recordings were obtained from seven leg muscles of the dominant leg and kinematic and kinetic features of the knee and hip joints were extracted.


Four motor modules were sufficient to represent the variety of behavioral goals demanded during robotic guidance, with similar relationships between muscle patterns and biomechanical parameters across subjects, confirming that the low-dimensional and impulsive control of human walking is maintained using robotic force guidance. The conditions of guidance force and speed that maintained correct and incorrect (not natural) modular control were identified.


In neurologically intact subjects robotic-guided walking at various force guidance and speed levels does not alter the basic locomotor control and timing. This allows the design of robotic-aided rehabilitation strategies aimed at the modulation of motor modules, which are altered in stroke.