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THINK: Toward Practical General-Purpose Brain-Computer Communication

Authors:

Mohit Agarwal,

Raghupathy SivakumarAuthors Info & Claims

HotWireless '15: Proceedings of the 2nd International Workshop on Hot Topics in Wireless

Pages 41 - 45

https://doi.org/10.1145/2799650.2799659

Published: 11 September 2015 Publication History

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Abstract

In this paper, we present \textbf{THINK}, a practical general-purpose brain-computer communication platform that relies on the OpenBCI and OpenViBE hardware and software platforms, and allows for a simple three-alphabet vocabulary. Specifically, we consider the scenario where a subject is wearing a sensor array (an electrode cap), and consciously manipulating her thoughts to communicate wirelessly with an external computing entity (a smartphone) without the aid of any external stimuli. Using \textbf{THINK}, we explore general aspects of brain computer communication that are application agnostic. In particular, we study the following questions: (i) what is the accuracy of the system? (ii) how fast can the subject switch thoughts corresponding to symbols; (iii) is there an impact on accuracy with learning time; and (iv) how does accuracy drop with decreasing number of sensors (electrodes)? Using purely experimental analysis, we present some results that provide preliminary answers for these questions.

References

[1]

Mark F. Bear, Barry W. Connors, and Michael A. Paradiso. Neuroscience: Exploring the Brain. 2015.

Google Scholar

[2]

John F. Walvoord. Daniel: The Key to Prophetic Revelation. John Wiley and Sons, 1989.

Google Scholar

[3]

H. Berger. "Uber das electrnkephalogramm des menchen". In: Arch Psychiatr Nervenkr 87 (1929), pp. 527--570.

Crossref

Google Scholar

[4]

Janis J Daly and Jonathan R Wolpaw. "Brain computer interfaces in neurological rehabilitation". In: The Lancent Neurology 7.11 (2008), pp. 1032--1043.

Crossref

Google Scholar

[5]

Ulrich Hoffmann et al. "An efficient P300-based brain computer interface for disabled subjects". In: Journal of Neuroscience Methods 167.1 (2008), pp. 115--125.

Crossref

Google Scholar

[6]

G. Pfurtscheller. "Event-related synchronization (ERS): an electrophysiological correlate of cortical areas at rest". In: Electroencephalography and Clinical Neuro- physiology 83.1 (1992), pp. 62--69.

Crossref

Google Scholar

[7]

G Pfurtscheller and A Aranibar. "Event-related cortical desynchronization detected by power measurements of scalp EEG". In: Electroencephalography and Clinical Neurophysiology 42.6 (1977), pp. 817--826.

Crossref

Google Scholar

[8]

Gert Pfurtscheller and Christa Neuper. "Motor imagery activates primary sensorimotor area in humans". In: Neuroscience Letters 239.2 -3 (1997), pp. 65--68.

Google Scholar

[9]

OpenBCI Hardware Module. http://www.openbci.com.

Google Scholar

[10]

Y. Renard et al. "OpenViBE: An Open-Source Software Platform to Design, Test, and Use Brain-Computer Interfaces in Real and Virtual Environments". In: tele-operators and virtual environments 19.1 (2010).

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Gupta ESivakumar R(2022)Wisdom of the Crowd: Using Multi-human Few-shot Learning to Improve Cross- User Generalization for Error Potentials in BCI Systems2022 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN55064.2022.9892115(1-8)Online publication date: 18-Jul-2022
https://doi.org/10.1109/IJCNN55064.2022.9892115
Xu DAgarwal MGupta EFekri FSivakumar R(2021)Accelerating Reinforcement Learning using EEG-based implicit human feedbackNeurocomputing10.1016/j.neucom.2021.06.064460(139-153)Online publication date: Oct-2021
https://doi.org/10.1016/j.neucom.2021.06.064
Agarwal MVenkateswaran SSivakumar RTran VAshok A(2020)Human-in-the-loop RL with an EEG wearable headsetProceedings of the 6th ACM Workshop on Wearable Systems and Applications10.1145/3396870.3400014(25-30)Online publication date: 19-Jun-2020
https://dl.acm.org/doi/10.1145/3396870.3400014
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THINK: Toward Practical General-Purpose Brain-Computer Communication

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Published In

HotWireless '15: Proceedings of the 2nd International Workshop on Hot Topics in Wireless

September 2015

58 pages

ISBN:9781450336994

DOI:10.1145/2799650

Program Chairs:
Ranveer Chandra
Microsoft Research
,
Kannan Srinivasan
The Ohio State University

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 11 September 2015

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National Science Foundation

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MobiCom'15

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SIGMOBILE

MobiCom'15: The 21th Annual International Conference on Mobile Computing and Networking

September 11, 2015

Paris, France

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HotWireless '15 Paper Acceptance Rate 10 of 16 submissions, 63%;

Overall Acceptance Rate 30 of 42 submissions, 71%

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Gupta ESivakumar R(2022)Wisdom of the Crowd: Using Multi-human Few-shot Learning to Improve Cross- User Generalization for Error Potentials in BCI Systems2022 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN55064.2022.9892115(1-8)Online publication date: 18-Jul-2022
https://doi.org/10.1109/IJCNN55064.2022.9892115
Xu DAgarwal MGupta EFekri FSivakumar R(2021)Accelerating Reinforcement Learning using EEG-based implicit human feedbackNeurocomputing10.1016/j.neucom.2021.06.064460(139-153)Online publication date: Oct-2021
https://doi.org/10.1016/j.neucom.2021.06.064
Agarwal MVenkateswaran SSivakumar RTran VAshok A(2020)Human-in-the-loop RL with an EEG wearable headsetProceedings of the 6th ACM Workshop on Wearable Systems and Applications10.1145/3396870.3400014(25-30)Online publication date: 19-Jun-2020
https://dl.acm.org/doi/10.1145/3396870.3400014
Agarwal MSivakumar RBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Charge for a whole day: Extending Battery Life for BCI Wearables using a Lightweight Wake-Up CommandProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376738(1-14)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376738
Gupta EAgarwal MSivakumar R(2020)Blink to Get In: Biometric Authentication for Mobile Devices using EEG SignalsICC 2020 - 2020 IEEE International Conference on Communications (ICC)10.1109/ICC40277.2020.9148741(1-6)Online publication date: Jun-2020
https://doi.org/10.1109/ICC40277.2020.9148741
Yohanandan SKiral-Kornek ITang JMshford BAsif UHarrer S(2018)A Robust Low-Cost EEG Motor Imagery-Based Brain-Computer Interface2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)10.1109/EMBC.2018.8513429(5089-5092)Online publication date: Jul-2018
https://doi.org/10.1109/EMBC.2018.8513429

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Brain-computer interface system using approximate entropy and EMD techniques

Understanding difficulty, your brain and challenge

Are low cost Brain Computer Interface headsets ready for motor imagery applications?

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