Multijoint error compensation mediates unstable object control.

نویسندگان

  • Tyler Cluff
  • Aspasia Manos
  • Timothy D Lee
  • Ramesh Balasubramaniam
چکیده

A key feature of skilled object control is the ability to correct performance errors. This process is not straightforward for unstable objects (e.g., inverted pendulum or "stick" balancing) because the mechanics of the object are sensitive to small control errors, which can lead to rapid performance changes. In this study, we have characterized joint recruitment and coordination processes in an unstable object control task. Our objective was to determine whether skill acquisition involves changes in the recruitment of individual joints or distributed error compensation. To address this problem, we monitored stick-balancing performance across four experimental sessions. We confirmed that subjects learned the task by showing an increase in the stability and length of balancing trials across training sessions. We demonstrated that motor learning led to the development of a multijoint error compensation strategy such that after training, subjects preferentially constrained joint angle variance that jeopardized task performance. The selective constraint of destabilizing joint angle variance was an important metric of motor learning. Finally, we performed a combined uncontrolled manifold-permutation analysis to ensure the variance structure was not confounded by differences in the variance of individual joint angles. We showed that reliance on multijoint error compensation increased, whereas individual joint variation (primarily at the wrist joint) decreased systematically with training. We propose a learning mechanism that is based on the accurate estimation of sensory states.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Different mechanisms involved in adaptation to stable and unstable dynamics.

Recently, we demonstrated that humans can learn to make accurate movements in an unstable environment by controlling magnitude, shape, and orientation of the endpoint impedance. Although previous studies of human motor learning suggest that the brain acquires an inverse dynamics model of the novel environment, it is not known whether this control mechanism is operative in unstable environments....

متن کامل

A Riemannian-Geometry Approach for Modeling and Control of Dynamics of Object Manipulation under Constraints

A Riemannian-geometry approach for modeling and control of dynamics of object manipulation under holonomic or nonholonomic constraints is presented. First, position/force hybrid control of an endeffector of a multijoint redundant (or nonredundant) robot under a holonomic constraint is reinterpreted in terms of “submersion” in Riemannian geometry. A force control signal constructed in the image ...

متن کامل

Spinal circuits can accommodate interaction torques during multijoint limb movements

The dynamic interaction of limb segments during movements that involve multiple joints creates torques in one joint due to motion about another. Evidence shows that such interaction torques are taken into account during the planning or control of movement in humans. Two alternative hypotheses could explain the compensation of these dynamic torques. One involves the use of internal models to cen...

متن کامل

Modelling and Compensation of uncertain time-delays in networked control systems with plant uncertainty using an Improved RMPC Method

Control systems with digital communication between sensors, controllers and actuators are called as Networked Control Systems (NCSs). In general, NCSs encounter with some problems such as packet dropouts and network induced delays. When plant uncertainty is added to the aforementioned problems, the design of the robust controller that is able to guarantee the stability, becomes more complex. In...

متن کامل

Design of Dual-high-order Dynamic Periodic Adaptive Learning Controller for Long-term Cogging Effect Compensation

Cogging effect is a serious disadvantage of the permanent magnetic synchronous motor (PMSM), and cogging force is a positiondependent periodic disturbance. In our previous work [1], a dual highorder periodic adaptive learning compensation (DHO-PALC) method for state-dependent periodic disturbance was presented, where the long term stability issue was not addressed. Due to the impact of the high...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Journal of neurophysiology

دوره 108 4  شماره 

صفحات  -

تاریخ انتشار 2012