Effect of added inertia on the pelvis on gait.
ABSTRACT Gait-training robots must display a low inertia in order to allow normal-looking walking. We studied the effect of inertia added to the pelvis during walking. We attached subjects to a mechanism that displays inertia to the pelvis in the anterior/posterior (AP) direction and the lateral direction independently. During walking we measured EMG, metabolic rate and kinematics of nine subjects. We found that inertias up to 5.3 kg added in lateral direction had no significant effect on gait. We found that 4.3 kg added in the AP direction had a significant but not relevant effect on the range of motion (RoM) of pelvis AP displacement and acceleration, and on hip flexion. 10.3 kg caused a significant and relevant difference in pelvis acceleration RoM. 6 kg is estimated as the maximum inertia that gait-training robots can add to the pelvis, without affecting the gait.
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ABSTRACT: When adapting to novel dynamic environments the nervous system learns to anticipate the imposed forces by forming an internal model of the environmental dynamics in a process driven by movement error reduction. Here, we tested the hypothesis that motor learning could be accelerated by transiently amplifying the environmental dynamics. A novel dynamic environment was created during treadmill stepping by applying a perpendicular viscous force field to the leg through a robotic device. The environmental dynamics were amplified by an amount determined by a computational learning model fit on a per-subject basis. On average, subjects significantly reduced the time required to predict the applied force field by approximately 26% when the field was transiently amplified. However, this reduction was not as great as that predicted by the model, likely due to nonstationarities in the learning parameters. We conclude that motor learning of a novel dynamic environment can be accelerated by exploiting the error-based learning mechanism of internal model formation, but that nonlinearities in adaptive response may limit the feasible acceleration. These results support an approach to movement training devices that amplify rather than reduce movement errors, and provide a computational framework for both implementing the approach and understanding its limitations.IEEE Transactions on Neural Systems and Rehabilitation Engineering 04/2005; · 3.26 Impact Factor
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ABSTRACT: "Assist as needed" control algorithms promote activity of patients during robotic gait training. Implementing these requires a free walking mode of a device, as unassisted motions should not be hindered. The goal of this study was to assess the normality of walking in the free walking mode of the LOPES gait trainer, an 8 degrees-of-freedom lightweight impedance controlled exoskeleton. Kinematics, gait parameters and muscle activity of walking in a free walking mode in the device were compared with those of walking freely on a treadmill. Average values and variability of the spatio-temporal gait variables showed no or small (relative to cycle-to-cycle variability) changes and the kinematics showed a significant and relevant decrease in knee angle range only. Muscles involved in push off showed a small decrease, whereas muscles involved in acceleration and deceleration of the swing leg showed an increase of their activity. Timing of the activity was mainly unaffected. Most of the observed differences could be ascribed to the inertia of the exoskeleton. Overall, walking with the LOPES resembled free walking, although this required several adaptations in muscle activity. These adaptations are such that we expect that Assist as Needed training can be implemented in LOPES.IEEE transactions on neural systems and rehabilitation engineering: a publication of the IEEE Engineering in Medicine and Biology Society 09/2008; 16(4):360-370. · 2.42 Impact Factor
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ABSTRACT: The metabolic cost of walking is determined by many mechanical tasks, but the individual contribution of each task remains unclear. We hypothesized that the force generated to support body weight and the work performed to redirect and accelerate body mass each individually incur a significant metabolic cost during normal walking. To test our hypothesis, we measured changes in metabolic rate in response to combinations of simulated reduced gravity and added loading. We found that reducing body weight by simulating reduced gravity modestly decreased net metabolic rate. By calculating the metabolic cost per Newton of reduced body weight, we deduced that generating force to support body weight comprises approximately 28% of the metabolic cost of normal walking. Similar to previous loading studies, we found that adding both weight and mass increased net metabolic rate in more than direct proportion to load. However, when we added mass alone by using a combination of simulated reduced gravity and added load, net metabolic rate increased about one-half as much as when we added both weight and mass. By calculating the cost per kilogram of added mass, we deduced that the work performed on the center of mass comprises approximately 45% of the metabolic cost of normal walking. Our findings support the hypothesis that force and work each incur a significant metabolic cost. Specifically, the cost of performing work to redirect and accelerate the center of mass is almost twice as great as the cost of generating force to support body weight.Journal of Applied Physiology 03/2005; 98(2):579-83. · 3.48 Impact Factor