High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton

Atilla Kilicarslan; Saurabh Prasad; Robert G. Grossman; Jose L. Contreras-Vidal

doi:10.1109/EMBC.2013.6610821

High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton

Atilla Kilicarslan, Saurabh Prasad, Robert G. Grossman, Jose L. Contreras-Vidal

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

175 Scopus citations

Abstract

Brain-Machine Interface (BMI) systems allow users to control external mechanical systems using their thoughts. Commonly used in literature are invasive techniques to acquire brain signals and decode user's attempted motions to drive these systems (e.g. a robotic manipulator). In this work we use a lower-body exoskeleton and measure the users brain activity using non-invasive electroencephalography (EEG). The main focus of this study is to decode a paraplegic subject's motion intentions and provide him with the ability of walking with a lower-body exoskeleton accordingly. We present our novel method of decoding with high offline evaluation accuracies (around 98%), our closed loop implementation structure with considerably short on-site training time (around 38 sec), and preliminary results from the real-time closed loop implementation (NeuroRex) with a paraplegic test subject.

Original language	English (US)
Title of host publication	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Pages	5606-5609
Number of pages	4
DOIs	https://doi.org/10.1109/EMBC.2013.6610821
State	Published - 2013
Event	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan Duration: Jul 3 2013 → Jul 7 2013

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Other

Other	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Country/Territory	Japan
City	Osaka
Period	7/3/13 → 7/7/13

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/EMBC.2013.6610821

Cite this

Kilicarslan, A., Prasad, S., Grossman, R. G., & Contreras-Vidal, J. L. (2013). High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 (pp. 5606-5609). Article 6610821 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2013.6610821

High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton. / Kilicarslan, Atilla; Prasad, Saurabh; Grossman, Robert G. et al.
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. p. 5606-5609 6610821 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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

Kilicarslan, A, Prasad, S, Grossman, RG & Contreras-Vidal, JL 2013, High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton. in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013., 6610821, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 5606-5609, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013, Osaka, Japan, 7/3/13. https://doi.org/10.1109/EMBC.2013.6610821

Kilicarslan A, Prasad S, Grossman RG, Contreras-Vidal JL. High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. p. 5606-5609. 6610821. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2013.6610821

Kilicarslan, Atilla ; Prasad, Saurabh ; Grossman, Robert G. et al. / High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. 2013. pp. 5606-5609 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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abstract = "Brain-Machine Interface (BMI) systems allow users to control external mechanical systems using their thoughts. Commonly used in literature are invasive techniques to acquire brain signals and decode user's attempted motions to drive these systems (e.g. a robotic manipulator). In this work we use a lower-body exoskeleton and measure the users brain activity using non-invasive electroencephalography (EEG). The main focus of this study is to decode a paraplegic subject's motion intentions and provide him with the ability of walking with a lower-body exoskeleton accordingly. We present our novel method of decoding with high offline evaluation accuracies (around 98%), our closed loop implementation structure with considerably short on-site training time (around 38 sec), and preliminary results from the real-time closed loop implementation (NeuroRex) with a paraplegic test subject.",

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High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton

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