Endpoint Stiffness of the Arm Is Directionally Tuned to Instability in the Environment

Franklin, David W.; Liaw, Gary; Milner, Theodore E.; Osu, Rieko; Burdet, Etienne; Kawato, Mitsuo

doi:10.1523/jneurosci.0968-07.2007

Cited by 277 publications

(257 citation statements)

References 45 publications

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“…During human reaching in the presence of expected mechanical perturbations (Burdet et al, 2001;Franklin et al, 2007), arm stiffness tends to increase compared with reaching without perturbations. The nervous system may respond to expected lower limb perturbations similarly.…”

Section: Introductionmentioning

confidence: 99%

Biomechanics and energetics of running on uneven terrain

Voloshina

Ferris

2015

Journal of Experimental Biology

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In the natural world, legged animals regularly run across uneven terrain with remarkable ease. To gain understanding of how running on uneven terrain affects the biomechanics and energetics of locomotion, we studied human subjects (N=12) running at 2.3 m s −1 on an uneven terrain treadmill, with up to a 2.5 cm height variation. We hypothesized that running on uneven terrain would show increased energy expenditure, step parameter variability and leg stiffness compared with running on smooth terrain. Subject energy expenditure increased by 5% (0.68 W kg −1 ; P<0.05) when running on uneven terrain compared with smooth terrain.Step width and length variability also increased by 27% and 26%, respectively (P<0.05). Positive and negative ankle work decreased on uneven terrain by 22% (0.413 J kg ), respectively (P=0.0001 and P=0.0008). Mean muscle activity increased on uneven terrain for three muscles in the thigh (P<0.05). Leg stiffness also increased by 20% (P<0.05) during running on uneven terrain compared with smooth terrain. Calculations of gravitational potential energy fluctuations suggest that about half of the energetic increases can be explained by additional positive and negative mechanical work for up and down steps on the uneven surface. This is consistent between walking and running, as the absolute increases in energetic cost for walking and running on uneven terrain were similar: 0.68 and 0.48 W kg −1 , respectively. These results provide insight into how surface smoothness can affect locomotion biomechanics and energetics in the real world.

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Section: Introductionmentioning

confidence: 99%

Biomechanics and energetics of running on uneven terrain

Voloshina

Ferris

2015

Journal of Experimental Biology

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“…This internal representation appears to be used for both feedforward (anticipatory) (Lackner and Dizio, 1994;Shadmehr and Mussa-Ivaldi, 1994;Flanagan and Wing, 1997;Krakauer et al, 1999;McIntyre et al, 2001;Singh and Scott, 2003) and feedback (Todorov and Jordan, 2002;Franklin et al, 2007;Kurtzer et al, 2008) control. Although there is some controversy as to whether the internal representation comprises inverse and/or forward models of the task dynamics (Ostry and Feldman, 2003;Pasalar et al, 2006;Yamamoto et al, 2007), it is clear that to ensure stable control when the environmental forces arise from unpredictability or mechanical instability it must also have the capacity to regulate mechanical impedance (Hogan, 1984;Burdet et al, 2001;Franklin et al, 2004Franklin et al, , 2007. Feedforward control of mechanical impedance is necessary in biological systems because neural delays preclude the use of feedback to compensate for instability in the environment (Mehta and Schaal, 2002).…”

Section: Introductionmentioning

confidence: 99%

CNS Learns Stable, Accurate, and Efficient Movements Using a Simple Algorithm

Franklin¹,

et al. 2008

Self Cite

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We propose a new model of motor learning to explain the exceptional dexterity and rapid adaptation to change, which characterize human motor control. It is based on the brain simultaneously optimizing stability, accuracy and efficiency. Formulated as a V-shaped learning function, it stipulates precisely how feedforward commands to individual muscles are adjusted based on error. Changes in muscle activation patterns recorded in experiments provide direct support for this control scheme. In simulated motor learning of novel environmental interactions, muscle activation, force and impedance evolved in a manner similar to humans, demonstrating its efficiency and plausibility. This model of motor learning offers new insights as to how the brain controls the complex musculoskeletal system and iteratively adjusts motor commands to improve motor skills with practice.

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“…For example, exerting forces against a screwdriver decreases limb stability in directions orthogonal to the driver, towards which buckling is possible, but not along the axis of the driver, which is extremely stiff relative to the arm. Feedforward motor commands can adapt to such direction dependent instabilities [4], but is it unclear if such specificity exists in reflex pathways providing feedback control.…”

Section: Introductionmentioning

confidence: 99%

Reflex modulation is linked to the orientation of arm mechanics relative to the environment

Krutky

Ravichandran

Trumbower

et al. 2008

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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To successfully complete a motor task, it is necessary to control not only the kinematics and dynamics of a limb, but also its mechanical properties. In a multijoint task such as the control of arm posture, limb mechanics are directional, resisting external disturbances more effectively in certain directions than others. It has been demonstrated that feedforward neuromotor pathways can regulate these directional characteristics of the arm to compensate for changes in the mechanical properties of the environment. However, it is unclear if spinal reflex pathways exhibit a similar specificity. The present results suggest that the sensitivity of the human stretch reflex also can be tuned to adapt the mechanical properties of the arm in a task appropriate manner. We hypothesized that the orientation of arm mechanics relative to the mechanical properties of the environment would influence reflex adaptation. Two destabilizing environments, oriented relative to the mechanical properties of the arm, were used to test this hypothesis. These environments were simulated using a 3 degrees of freedom (DOF) robot, which also was used to perturb arm posture. The resulting reflexes, assessed by electromyograms recorded from 8 muscles, were found to modulate in accordance with how the environmental instability was oriented relative to the mechanical properties of the arm. Our results suggest that stretch sensitive reflexes throughout the arm are modulated in a coordinated manner corresponding to the orientation of arm mechanics relative to the environment.

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Endpoint Stiffness of the Arm Is Directionally Tuned to Instability in the Environment

Cited by 277 publications

References 45 publications

Biomechanics and energetics of running on uneven terrain

Biomechanics and energetics of running on uneven terrain

CNS Learns Stable, Accurate, and Efficient Movements Using a Simple Algorithm

Reflex modulation is linked to the orientation of arm mechanics relative to the environment

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