Optimal human-in-the-loop interfaces based on Maxwell's Demon

Kathleen Fitzsimons; Emmanouil Tzorakoleftherakis; Todd D. Murphey

doi:10.1109/ACC.2016.7525614

Optimal human-in-the-loop interfaces based on Maxwell's Demon

Kathleen Fitzsimons
, Emmanouil Tzorakoleftherakis
, Todd D. Murphey

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Scopus citations

Abstract

Interactions with complex systems require safe and reliable interfaces. However, such interfaces must be able to account for substantial uncertainty resulting from the unpredictable nature of human behavior. In this study we demonstrate that a controller/filter unit operating as a Maxwell's Demon can be used to synthesize human-machine interfaces that effectively filter user input in real time. Our Maxwell's Demon Algorithm (MDA) was applied in mechanical and software filtering of user actions for the cart-pendulum inversion task. Software filtering was implemented and tested using a custom Android application. Additionally, a haptic device was employed to create a mechanical filter. Results from nine healthy subjects show that both software and mechanical filters increased the success rate of subjects in the swing-up task. This result suggests that the MDA may be applied to design reliable human-machine interfaces for rehabilitation, training, teleoperation and other shared control tasks.

Original language	English (US)
Title of host publication	2016 American Control Conference, ACC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4397-4402
Number of pages	6
ISBN (Electronic)	9781467386821
DOIs	https://doi.org/10.1109/ACC.2016.7525614
State	Published - Jul 28 2016
Event	2016 American Control Conference, ACC 2016 - Boston, United States Duration: Jul 6 2016 → Jul 8 2016

Publication series

Name	Proceedings of the American Control Conference
Volume	2016-July
ISSN (Print)	0743-1619

Other

Other	2016 American Control Conference, ACC 2016
Country/Territory	United States
City	Boston
Period	7/6/16 → 7/8/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.1109/ACC.2016.7525614

Cite this

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title = "Optimal human-in-the-loop interfaces based on Maxwell's Demon",

abstract = "Interactions with complex systems require safe and reliable interfaces. However, such interfaces must be able to account for substantial uncertainty resulting from the unpredictable nature of human behavior. In this study we demonstrate that a controller/filter unit operating as a Maxwell's Demon can be used to synthesize human-machine interfaces that effectively filter user input in real time. Our Maxwell's Demon Algorithm (MDA) was applied in mechanical and software filtering of user actions for the cart-pendulum inversion task. Software filtering was implemented and tested using a custom Android application. Additionally, a haptic device was employed to create a mechanical filter. Results from nine healthy subjects show that both software and mechanical filters increased the success rate of subjects in the swing-up task. This result suggests that the MDA may be applied to design reliable human-machine interfaces for rehabilitation, training, teleoperation and other shared control tasks.",

author = "Kathleen Fitzsimons and Emmanouil Tzorakoleftherakis and Murphey, \{Todd D.\}",

note = "Publisher Copyright: {\textcopyright} 2016 American Automatic Control Council (AACC).; 2016 American Control Conference, ACC 2016 ; Conference date: 06-07-2016 Through 08-07-2016",

year = "2016",

month = jul,

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doi = "10.1109/ACC.2016.7525614",

language = "English (US)",

series = "Proceedings of the American Control Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2016 American Control Conference, ACC 2016",

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Fitzsimons, K, Tzorakoleftherakis, E & Murphey, TD 2016, Optimal human-in-the-loop interfaces based on Maxwell's Demon. in 2016 American Control Conference, ACC 2016., 7525614, Proceedings of the American Control Conference, vol. 2016-July, Institute of Electrical and Electronics Engineers Inc., pp. 4397-4402, 2016 American Control Conference, ACC 2016, Boston, United States, 7/6/16. https://doi.org/10.1109/ACC.2016.7525614

Optimal human-in-the-loop interfaces based on Maxwell's Demon. / Fitzsimons, Kathleen; Tzorakoleftherakis, Emmanouil; Murphey, Todd D.
2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 4397-4402 7525614 (Proceedings of the American Control Conference; Vol. 2016-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Optimal human-in-the-loop interfaces based on Maxwell's Demon

AU - Fitzsimons, Kathleen

AU - Tzorakoleftherakis, Emmanouil

AU - Murphey, Todd D.

PY - 2016/7/28

Y1 - 2016/7/28

N2 - Interactions with complex systems require safe and reliable interfaces. However, such interfaces must be able to account for substantial uncertainty resulting from the unpredictable nature of human behavior. In this study we demonstrate that a controller/filter unit operating as a Maxwell's Demon can be used to synthesize human-machine interfaces that effectively filter user input in real time. Our Maxwell's Demon Algorithm (MDA) was applied in mechanical and software filtering of user actions for the cart-pendulum inversion task. Software filtering was implemented and tested using a custom Android application. Additionally, a haptic device was employed to create a mechanical filter. Results from nine healthy subjects show that both software and mechanical filters increased the success rate of subjects in the swing-up task. This result suggests that the MDA may be applied to design reliable human-machine interfaces for rehabilitation, training, teleoperation and other shared control tasks.

AB - Interactions with complex systems require safe and reliable interfaces. However, such interfaces must be able to account for substantial uncertainty resulting from the unpredictable nature of human behavior. In this study we demonstrate that a controller/filter unit operating as a Maxwell's Demon can be used to synthesize human-machine interfaces that effectively filter user input in real time. Our Maxwell's Demon Algorithm (MDA) was applied in mechanical and software filtering of user actions for the cart-pendulum inversion task. Software filtering was implemented and tested using a custom Android application. Additionally, a haptic device was employed to create a mechanical filter. Results from nine healthy subjects show that both software and mechanical filters increased the success rate of subjects in the swing-up task. This result suggests that the MDA may be applied to design reliable human-machine interfaces for rehabilitation, training, teleoperation and other shared control tasks.

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M3 - Conference contribution

AN - SCOPUS:84992146144

T3 - Proceedings of the American Control Conference

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BT - 2016 American Control Conference, ACC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 American Control Conference, ACC 2016

Y2 - 6 July 2016 through 8 July 2016

ER -

Optimal human-in-the-loop interfaces based on Maxwell's Demon

Abstract

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UN SDGs

All Science Journal Classification (ASJC) codes

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