I Meant to Do That: Determining the Intentions of Action in the Face of Disturbances.
Our actions often do not match our intentions when there are external disturbances such as turbulence. We derived a novel modeling approach for determining this motor intent from targeted reaching motions that are disturbed by an unexpected force. First, we demonstrated how to mathematically invert...
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doaj-603118448c1f4dd1b926cad5e8effaaf2020-11-25T02:47:03ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01109e013728910.1371/journal.pone.0137289I Meant to Do That: Determining the Intentions of Action in the Face of Disturbances.Justin HorowitzJames PattonOur actions often do not match our intentions when there are external disturbances such as turbulence. We derived a novel modeling approach for determining this motor intent from targeted reaching motions that are disturbed by an unexpected force. First, we demonstrated how to mathematically invert both feedforward (predictive) and feedback controls to obtain an intended trajectory. We next examined the model's sensitivity to a realistic range of parameter uncertainties, and found that the expected inaccuracy due to all possible parameter mis-estimations was less than typical movement-to-movement variations seen when humans reach to similar targets. The largest sensitivity arose mainly from uncertainty in joint stiffnesses. Humans cannot change their intent until they acquire sensory feedback, therefore we tested the hypothesis that a straight-line intent should be evident for at least the first 120 milliseconds following the onset of a disturbance. As expected, the intended trajectory showed no change from undisturbed reaching for more than 150 milliseconds after the disturbance onset. Beyond this point, however, we detected a change in intent in five out of eight subjects, surprisingly even when the hand is already near the target. Knowing such an intent signal is broadly applicable: enhanced human-machine interaction, the study of impaired intent in neural disorders, the real-time determination (and manipulation) of error in training, and complex systems that embody planning such as brain machine interfaces, team sports, crowds, or swarms. In addition, observing intent as it changes might act as a window into the mechanisms of planning, correction, and learning.http://europepmc.org/articles/PMC4556620?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Justin Horowitz James Patton |
spellingShingle |
Justin Horowitz James Patton I Meant to Do That: Determining the Intentions of Action in the Face of Disturbances. PLoS ONE |
author_facet |
Justin Horowitz James Patton |
author_sort |
Justin Horowitz |
title |
I Meant to Do That: Determining the Intentions of Action in the Face of Disturbances. |
title_short |
I Meant to Do That: Determining the Intentions of Action in the Face of Disturbances. |
title_full |
I Meant to Do That: Determining the Intentions of Action in the Face of Disturbances. |
title_fullStr |
I Meant to Do That: Determining the Intentions of Action in the Face of Disturbances. |
title_full_unstemmed |
I Meant to Do That: Determining the Intentions of Action in the Face of Disturbances. |
title_sort |
i meant to do that: determining the intentions of action in the face of disturbances. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2015-01-01 |
description |
Our actions often do not match our intentions when there are external disturbances such as turbulence. We derived a novel modeling approach for determining this motor intent from targeted reaching motions that are disturbed by an unexpected force. First, we demonstrated how to mathematically invert both feedforward (predictive) and feedback controls to obtain an intended trajectory. We next examined the model's sensitivity to a realistic range of parameter uncertainties, and found that the expected inaccuracy due to all possible parameter mis-estimations was less than typical movement-to-movement variations seen when humans reach to similar targets. The largest sensitivity arose mainly from uncertainty in joint stiffnesses. Humans cannot change their intent until they acquire sensory feedback, therefore we tested the hypothesis that a straight-line intent should be evident for at least the first 120 milliseconds following the onset of a disturbance. As expected, the intended trajectory showed no change from undisturbed reaching for more than 150 milliseconds after the disturbance onset. Beyond this point, however, we detected a change in intent in five out of eight subjects, surprisingly even when the hand is already near the target. Knowing such an intent signal is broadly applicable: enhanced human-machine interaction, the study of impaired intent in neural disorders, the real-time determination (and manipulation) of error in training, and complex systems that embody planning such as brain machine interfaces, team sports, crowds, or swarms. In addition, observing intent as it changes might act as a window into the mechanisms of planning, correction, and learning. |
url |
http://europepmc.org/articles/PMC4556620?pdf=render |
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