http://www.jneuroengrehab.com/content/9/1/76/abstract
Abstract (provisional)
Background
It is hypothesized that locomotion is achieved by means of rhythm generating networks
(central pattern generators) and muscle activation generating networks. This modular
organization can be partly identified from the analysis of the muscular activity by
means of factorization algorithms. The activity of rhythm generating networks is described
by activation signals whilst the muscle intervention generating network is represented
by motor modules (muscle synergies). In this study, we extend the analysis of modular
organization of walking to the case of robot-aided locomotion, at varying speed and
body weight support level.
Methods
Non Negative Matrix Factorization was applied on surface electromyographic signals
of 8 lower limb muscles of healthy subjects walking in gait robotic trainer at different
walking velocities (1 to 3km/h) and levels of body weight support (0 to 30%).
Results
The muscular activity of volunteers could be described by low dimensionality (4 modules),
as for overground walking. Moreover, the activation signals during robot-aided walking
were bursts of activation timed at specific phases of the gait cycle, underlying an
impulsive controller, as also observed in overground walking. This modular organization
was consistent across the investigated speeds, body weight support level, and subjects.
Conclusions
These results indicate that walking in a Lokomat robotic trainer is achieved by similar
motor modules and activation signals as overground walking and thus supports the use
of robotic training for re-establishing natural walking patterns.
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