Neuromechanics of a Button Press

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Neuromechanics of a Button Press. / Oulasvirta, Antti; Kim, Sunjun; Lee, Byungjoo.

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. New York, NY, USA : ACM, 2018.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Oulasvirta, A, Kim, S & Lee, B 2018, Neuromechanics of a Button Press. in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, ACM SIGCHI Annual Conference on Human Factors in Computing Systems, Montreal, Canada, 21/04/2018. https://doi.org/10.1145/3173574.3174082

APA

Oulasvirta, A., Kim, S., & Lee, B. (2018). Neuromechanics of a Button Press. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems New York, NY, USA: ACM. https://doi.org/10.1145/3173574.3174082

Vancouver

Oulasvirta A, Kim S, Lee B. Neuromechanics of a Button Press. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM. 2018 https://doi.org/10.1145/3173574.3174082

Author

Oulasvirta, Antti ; Kim, Sunjun ; Lee, Byungjoo. / Neuromechanics of a Button Press. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. New York, NY, USA : ACM, 2018.

Bibtex - Download

@inproceedings{8c49d77a1c464ea6b25b96d26c58d7ee,
title = "Neuromechanics of a Button Press",
abstract = "To press a button, a finger must push down and pull up with the right force and timing. How the motor system succeeds in button-pressing, in spite of neural noise and lacking direct access to the mechanism of the button, is poorly understood. This paper investigates a unifying account based on neuromechanics. Mechanics is used to model muscles controlling the finger that contacts the button. Neurocognitive principles are used to model how the motor system learns appropriate muscle activations over repeated strokes though relying on degraded sensory feedback. Neuromechanical simulations yield a rich set of predictions for kinematics, dynamics, and user performance and may aid in understanding and improving input devices. We present a computational implementation and evaluate predictions for common button types.",
keywords = "Buttons, input devices, neuromechanics, perceptual control, control theory, probabilistic motor control, input engineering",
author = "Antti Oulasvirta and Sunjun Kim and Byungjoo Lee",
note = "| openaire: EC/H2020/637991/EU//COMPUTED",
year = "2018",
doi = "10.1145/3173574.3174082",
language = "English",
isbn = "978-1-4503-5620-6",
booktitle = "Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems",
publisher = "ACM",

}

RIS - Download

TY - GEN

T1 - Neuromechanics of a Button Press

AU - Oulasvirta, Antti

AU - Kim, Sunjun

AU - Lee, Byungjoo

N1 - | openaire: EC/H2020/637991/EU//COMPUTED

PY - 2018

Y1 - 2018

N2 - To press a button, a finger must push down and pull up with the right force and timing. How the motor system succeeds in button-pressing, in spite of neural noise and lacking direct access to the mechanism of the button, is poorly understood. This paper investigates a unifying account based on neuromechanics. Mechanics is used to model muscles controlling the finger that contacts the button. Neurocognitive principles are used to model how the motor system learns appropriate muscle activations over repeated strokes though relying on degraded sensory feedback. Neuromechanical simulations yield a rich set of predictions for kinematics, dynamics, and user performance and may aid in understanding and improving input devices. We present a computational implementation and evaluate predictions for common button types.

AB - To press a button, a finger must push down and pull up with the right force and timing. How the motor system succeeds in button-pressing, in spite of neural noise and lacking direct access to the mechanism of the button, is poorly understood. This paper investigates a unifying account based on neuromechanics. Mechanics is used to model muscles controlling the finger that contacts the button. Neurocognitive principles are used to model how the motor system learns appropriate muscle activations over repeated strokes though relying on degraded sensory feedback. Neuromechanical simulations yield a rich set of predictions for kinematics, dynamics, and user performance and may aid in understanding and improving input devices. We present a computational implementation and evaluate predictions for common button types.

KW - Buttons

KW - input devices

KW - neuromechanics

KW - perceptual control

KW - control theory

KW - probabilistic motor control

KW - input engineering

U2 - 10.1145/3173574.3174082

DO - 10.1145/3173574.3174082

M3 - Conference contribution

SN - 978-1-4503-5620-6

BT - Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

PB - ACM

CY - New York, NY, USA

ER -

ID: 17267944