Several robotic devices have been developed for the rehabilitation of treadmill walking in patients with movement disorders due to injuries or diseases of the central nervous system. These robots induce coordinated multi-joint movements aimed at reproducing the physiological walking or stepping patterns. Control strategies developed for robotic locomotor training need a set of predefined lower limb joint angular trajectories as reference input for the control algorithm. Such trajectories are typically taken from normative database of overground unassisted walking. However, it has been demonstrated that gait speed and the amount of body weight support significantly influence joint trajectories during walking. Moreover, both the speed and the level of body weight support must be individually adjusted according to the rehabilitation phase and the residual locomotor abilities of the patient. In this work, 10 healthy participants (age range: 23-48 years) were asked to walk in movement analysis laboratory on a treadmill at five different speeds and four different levels of body weight support; besides, a trial with full body weight support, that is, with the subject suspended on air, was performed at two different cadences. The results confirm that lower limb kinematics during walking is affected by gait speed and by the amount of body weight support, and that on-air stepping is radically different from treadmill walking. Importantly, the results provide normative data in a numerical form to be used as reference trajectories for controlling robot-assisted body weight support walking training. An electronic addendum is provided to easily access to such reference data for different combinations of gait speeds and body weight support levels.

Influence of the amount of body weight support on lower limb joints' kinematics during treadmill walking at different gait speeds: Reference data on healthy adults to define trajectories for robot assistance

Geda, Elisabetta;Bruno, Valentina;Sacco, Katiuscia
2018-01-01

Abstract

Several robotic devices have been developed for the rehabilitation of treadmill walking in patients with movement disorders due to injuries or diseases of the central nervous system. These robots induce coordinated multi-joint movements aimed at reproducing the physiological walking or stepping patterns. Control strategies developed for robotic locomotor training need a set of predefined lower limb joint angular trajectories as reference input for the control algorithm. Such trajectories are typically taken from normative database of overground unassisted walking. However, it has been demonstrated that gait speed and the amount of body weight support significantly influence joint trajectories during walking. Moreover, both the speed and the level of body weight support must be individually adjusted according to the rehabilitation phase and the residual locomotor abilities of the patient. In this work, 10 healthy participants (age range: 23-48 years) were asked to walk in movement analysis laboratory on a treadmill at five different speeds and four different levels of body weight support; besides, a trial with full body weight support, that is, with the subject suspended on air, was performed at two different cadences. The results confirm that lower limb kinematics during walking is affected by gait speed and by the amount of body weight support, and that on-air stepping is radically different from treadmill walking. Importantly, the results provide normative data in a numerical form to be used as reference trajectories for controlling robot-assisted body weight support walking training. An electronic addendum is provided to easily access to such reference data for different combinations of gait speeds and body weight support levels.
2018
232
6
619
627
Body weight support; gait kinematics; on-air stepping; robot assisted-gait rehabilitation; treadmill training
Ferrarin, Maurizio; Rabuffetti, Marco; Geda, Elisabetta; Sirolli, Silvia; Marzegan, Alberto; Bruno, Valentina; Sacco, Katiuscia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1730413
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