Robust communication with IoT devices using wearable brain machine interfaces

Md Muztoba, Ujjwal Gupta, Tanvir Mustofa, Umit Ogras

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Proliferation of internet-of-things (IoT) will lead to scenarios where humans will interact with and control a variety of networked devices including sensors and actuators. Wearable brain-machine interfaces (BMI) can be a key enabler of this interaction for people with disabilities and limited motor skills. At the same time, BMI can improve the experience of healthy individuals significantly. However, state-of-the-art BMI systems have limited applicability as they are prone to errors even with sophisticated machine learning algorithms used for classifying the electroencephalogram (EEG) signals. We improve the reliability of BMI communication significantly by proposing two techniques at higher abstraction layers. Our first contribution is a command confirmation protocol that protects the brain-machine communication against false interpretations at run time. The second contribution is an off-line optimal event selection algorithm that identifies the most reliable subset of events supported by the target BMI system. The event selection is guided by novel user specific reliability metrics defined for the first time in this paper. Extensive experiments using a commercial BMI system demonstrate that the proposed techniques increase the communication robustness significantly, and reduce the time to complete a complex navigation task by 63% on average.

Original languageEnglish (US)
Title of host publication2015 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages200-207
Number of pages8
ISBN (Electronic)9781467383882
DOIs
StatePublished - Jan 5 2016
Event34th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015 - Austin, United States
Duration: Nov 2 2015Nov 6 2015

Other

Other34th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015
CountryUnited States
CityAustin
Period11/2/1511/6/15

Fingerprint

Brain
Communication
Electroencephalography
Internet of things
Set theory
Learning algorithms
Learning systems
Navigation
Actuators
Network protocols
Sensors
Experiments

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

Cite this

Muztoba, M., Gupta, U., Mustofa, T., & Ogras, U. (2016). Robust communication with IoT devices using wearable brain machine interfaces. In 2015 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015 (pp. 200-207). [7372571] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCAD.2015.7372571

Robust communication with IoT devices using wearable brain machine interfaces. / Muztoba, Md; Gupta, Ujjwal; Mustofa, Tanvir; Ogras, Umit.

2015 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 200-207 7372571.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Muztoba, M, Gupta, U, Mustofa, T & Ogras, U 2016, Robust communication with IoT devices using wearable brain machine interfaces. in 2015 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015., 7372571, Institute of Electrical and Electronics Engineers Inc., pp. 200-207, 34th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015, Austin, United States, 11/2/15. https://doi.org/10.1109/ICCAD.2015.7372571
Muztoba M, Gupta U, Mustofa T, Ogras U. Robust communication with IoT devices using wearable brain machine interfaces. In 2015 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 200-207. 7372571 https://doi.org/10.1109/ICCAD.2015.7372571
Muztoba, Md ; Gupta, Ujjwal ; Mustofa, Tanvir ; Ogras, Umit. / Robust communication with IoT devices using wearable brain machine interfaces. 2015 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2015. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 200-207
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