scholarly journals Adaptive use of interaction torque during arm reaching movement from the optimal control viewpoint

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Van Hoan Vu ◽  
Brice Isableu ◽  
Bastien Berret
Keyword(s):  
Optimal Control ◽  
Interaction Torque ◽  
Reaching Movement ◽  
Adaptive Use ◽  
Arm Reaching

Evaluation of Power-Assist System by Computer Simulation

2016 ◽  
Vol 20 (3) ◽  
pp. 477-483 ◽  
Author(s):  
Yoshiaki Taniai ◽  
◽  
Tomohide Naniwa ◽  
Yasutake Takahashi ◽  
Masayuki Kawai
Keyword(s):  
Computer Simulation ◽  
Evaluation Framework ◽  
Metabolic Energy ◽  
Evaluation Index ◽  
Optimality Principle ◽  
Upper Arm ◽  
Reaching Movement ◽  
Effective Power ◽  
Arm Reaching ◽  
Motor Paralysis

Powered exoskeletons have been proposed and developed in various works with the aim of compensating for motor paralysis or reducing weight, workload, or metabolic energy consumption. However, development of the power-assist system depends on the development and evaluation of real powered exoskeletons, and few studies have evaluated the performance of the power-assist system by means of computer simulation. In this paper, we propose an evaluation framework based on computer simulation for the development of an effective power-assist system and demonstrate an analysis of a power-assisted upper-arm reaching movement. We employed the optimality principle to obtain the adapted movements of humans for power-assist systems and compared the performances of power- and non-power-assisted movements in terms of the evaluation index of the power-assist system.

scholarly journals The duration of reaching movement is longer than predicted by minimum variance

2016 ◽  
Vol 116 (5) ◽  
pp. 2342-2345 ◽  
Author(s):  
Chunji Wang ◽  
Yupeng Xiao ◽  
Etienne Burdet ◽  
James Gordon ◽  
Nicolas Schweighofer
Keyword(s):  
Minimum Variance ◽  
Reaching Movements ◽  
Movement Duration ◽  
Slow Movement ◽  
Reaching Movement ◽  
End Point ◽  
Parsimonious Explanation ◽  
Arm Reaching ◽  
The Central Nervous System ◽  
Duration Condition

Whether the central nervous system minimizes variability or effort in planning arm movements can be tested by measuring the preferred movement duration and end-point variability. Here we conducted an experiment in which subjects performed arm reaching movements without visual feedback in fast-, medium-, slow-, and preferred-duration conditions. Results show that 1) total end-point variance was smallest in the medium-duration condition and 2) subjects preferred to carry out movements that were slower than this medium-duration condition. A parsimonious explanation for the overall pattern of end-point errors across fast, medium, preferred, and slow movement durations is that movements are planned to minimize effort as well as end-point error due to both signal-dependent and constant noise.

Online gain update for manual following response accompanied by gaze shift during arm reaching

2015 ◽  
Vol 113 (4) ◽  
pp. 1206-1216 ◽  
Author(s):  
Naotoshi Abekawa ◽  
Hiroaki Gomi
Keyword(s):  
Continuous Monitoring ◽  
Visual Motion ◽  
Target Location ◽  
Body Movement ◽  
Gaze Shift ◽  
Reaching Movement ◽  
The Gaze ◽  
Arm Reaching ◽  
Online Corrections ◽  
The Brain

To capture objects by hand, online motor corrections are required to compensate for self-body movements. Recent studies have shown that background visual motion, usually caused by body movement, plays a significant role in such online corrections. Visual motion applied during a reaching movement induces a rapid and automatic manual following response (MFR) in the direction of the visual motion. Importantly, the MFR amplitude is modulated by the gaze direction relative to the reach target location (i.e., foveal or peripheral reaching). That is, the brain specifies the adequate visuomotor gain for an online controller based on gaze-reach coordination. However, the time or state point at which the brain specifies this visuomotor gain remains unclear. More specifically, does the gain change occur even during the execution of reaching? In the present study, we measured MFR amplitudes during a task in which the participant performed a saccadic eye movement that altered the gaze-reach coordination during reaching. The results indicate that the MFR amplitude immediately after the saccade termination changed according to the new gaze-reach coordination, suggesting a flexible online updating of the MFR gain during reaching. An additional experiment showed that this gain updating mostly started before the saccade terminated. Therefore, the MFR gain updating process would be triggered by an ocular command related to saccade planning or execution based on forthcoming changes in the gaze-reach coordination. Our findings suggest that the brain flexibly updates the visuomotor gain for an online controller even during reaching movements based on continuous monitoring of the gaze-reach coordination.

Optimal control of reaching includes kinematic constraints

2013 ◽  
Vol 110 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Michael Mistry ◽  
Evangelos Theodorou ◽  
Stefan Schaal ◽  
Mitsuo Kawato
Keyword(s):  
Optimal Control ◽  
Stochastic Optimal Control ◽  
Optimal Control Theory ◽  
Internal Model ◽  
Reaching Movement ◽  
Reaching Task ◽  
Hand Trajectory ◽  
Curved Trajectories ◽  
Hand Off ◽  
Directional Preference

We investigate adaptation under a reaching task with an acceleration-based force field perturbation designed to alter the nominal straight hand trajectory in a potentially benign manner: pushing the hand off course in one direction before subsequently restoring towards the target. In this particular task, an explicit strategy to reduce motor effort requires a distinct deviation from the nominal rectilinear hand trajectory. Rather, our results display a clear directional preference during learning, as subjects adapted perturbed curved trajectories towards their initial baselines. We model this behavior using the framework of stochastic optimal control theory and an objective function that trades off the discordant requirements of 1) target accuracy, 2) motor effort, and 3) kinematic invariance. Our work addresses the underlying objective of a reaching movement, and we suggest that robustness, particularly against internal model uncertainly, is as essential to the reaching task as terminal accuracy and energy efficiency.

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