Brain computer interface for gesture control of a social robot: An offline study

Reza Abiri; Xiaopeng Zhao; Griffin Heise; Yang Jiang; Fateme Abiri

doi:10.1109/IranianCEE.2017.7985231

Brain computer interface for gesture control of a social robot: An offline study

Reza Abiri, Xiaopeng Zhao, Griffin Heise, Yang Jiang, Fateme Abiri

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

13 Scopus citations

Abstract

Brain computer interface (BCI) provides promising applications in neuroprosthesis and neurorehabilitation by controlling computers and robotic devices based on the patient's intentions. Here, we have developed a novel BCI platform that controls a personalized social robot using noninvasively acquired brain signals. Scalp electroencephalogram (EEG) signals are collected from a user in real-time during tasks of imaginary movements. The imagined body kinematics are decoded using a regression model to calculate the user-intended velocity. Then, the decoded kinematic information is mapped to control the gestures of a social robot. The platform here may be utilized as a human-robot-interaction framework by combining with neurofeedback mechanisms to enhance the cognitive capability of persons with dementia.

Original language	English
Title of host publication	2017 25th Iranian Conference on Electrical Engineering, ICEE 2017
Pages	113-117
Number of pages	5
ISBN (Electronic)	9781509059638
DOIs	https://doi.org/10.1109/IranianCEE.2017.7985231
State	Published - Jul 19 2017
Event	25th Iranian Conference on Electrical Engineering, ICEE 2017 - Tehran, Iran, Islamic Republic of Duration: May 2 2017 → May 4 2017

Publication series

Name	2017 25th Iranian Conference on Electrical Engineering, ICEE 2017

Conference

Conference	25th Iranian Conference on Electrical Engineering, ICEE 2017
Country/Territory	Iran, Islamic Republic of
City	Tehran
Period	5/2/17 → 5/4/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

Brain Computer Interface
EEG
Human-Robot Interaction
Social Robot

ASJC Scopus subject areas

Electrical and Electronic Engineering
Control and Optimization
Energy Engineering and Power Technology

Access to Document

10.1109/IranianCEE.2017.7985231

Cite this

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title = "Brain computer interface for gesture control of a social robot: An offline study",

abstract = "Brain computer interface (BCI) provides promising applications in neuroprosthesis and neurorehabilitation by controlling computers and robotic devices based on the patient's intentions. Here, we have developed a novel BCI platform that controls a personalized social robot using noninvasively acquired brain signals. Scalp electroencephalogram (EEG) signals are collected from a user in real-time during tasks of imaginary movements. The imagined body kinematics are decoded using a regression model to calculate the user-intended velocity. Then, the decoded kinematic information is mapped to control the gestures of a social robot. The platform here may be utilized as a human-robot-interaction framework by combining with neurofeedback mechanisms to enhance the cognitive capability of persons with dementia.",

keywords = "Brain Computer Interface, EEG, Human-Robot Interaction, Social Robot",

author = "Reza Abiri and Xiaopeng Zhao and Griffin Heise and Yang Jiang and Fateme Abiri",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 25th Iranian Conference on Electrical Engineering, ICEE 2017 ; Conference date: 02-05-2017 Through 04-05-2017",

year = "2017",

month = jul,

day = "19",

doi = "10.1109/IranianCEE.2017.7985231",

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Abiri, R, Zhao, X, Heise, G, Jiang, Y & Abiri, F 2017, Brain computer interface for gesture control of a social robot: An offline study. in 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017., 7985231, 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, pp. 113-117, 25th Iranian Conference on Electrical Engineering, ICEE 2017, Tehran, Iran, Islamic Republic of, 5/2/17. https://doi.org/10.1109/IranianCEE.2017.7985231

Brain computer interface for gesture control of a social robot: An offline study. / Abiri, Reza; Zhao, Xiaopeng; Heise, Griffin et al.
2017 25th Iranian Conference on Electrical Engineering, ICEE 2017. 2017. p. 113-117 7985231 (2017 25th Iranian Conference on Electrical Engineering, ICEE 2017).

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

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AU - Abiri, Reza

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AU - Heise, Griffin

AU - Jiang, Yang

AU - Abiri, Fateme

PY - 2017/7/19

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N2 - Brain computer interface (BCI) provides promising applications in neuroprosthesis and neurorehabilitation by controlling computers and robotic devices based on the patient's intentions. Here, we have developed a novel BCI platform that controls a personalized social robot using noninvasively acquired brain signals. Scalp electroencephalogram (EEG) signals are collected from a user in real-time during tasks of imaginary movements. The imagined body kinematics are decoded using a regression model to calculate the user-intended velocity. Then, the decoded kinematic information is mapped to control the gestures of a social robot. The platform here may be utilized as a human-robot-interaction framework by combining with neurofeedback mechanisms to enhance the cognitive capability of persons with dementia.

AB - Brain computer interface (BCI) provides promising applications in neuroprosthesis and neurorehabilitation by controlling computers and robotic devices based on the patient's intentions. Here, we have developed a novel BCI platform that controls a personalized social robot using noninvasively acquired brain signals. Scalp electroencephalogram (EEG) signals are collected from a user in real-time during tasks of imaginary movements. The imagined body kinematics are decoded using a regression model to calculate the user-intended velocity. Then, the decoded kinematic information is mapped to control the gestures of a social robot. The platform here may be utilized as a human-robot-interaction framework by combining with neurofeedback mechanisms to enhance the cognitive capability of persons with dementia.

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KW - Social Robot

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Brain computer interface for gesture control of a social robot: An offline study

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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