Evaluation of a minimally invasive endovascular neural interface for decoding motor activity

Ian A. Forsyth; Megan Dunston; Gabriel Lombardi; Gil S. Rind; Stephen Ronayne; Yan T. Wong; Clive N. May; David B. Grayden; Thomas Oxley; Nicholas Opie; Sam E. John

doi:10.1109/NER.2019.8717000

Evaluation of a minimally invasive endovascular neural interface for decoding motor activity

Ian A. Forsyth, Megan Dunston, Gabriel Lombardi, Gil S. Rind, Stephen Ronayne, Yan T. Wong, Clive N. May, David B. Grayden, Thomas Oxley, Nicholas Opie, Sam E. John

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

15 Citations (Scopus)

Abstract

Endovascular devices like the Stentrode™ provide a minimally invasive approach to brain-machine-interfaces that mitigates safety concerns while maintaining good signal quality. Our research aims to evaluate the feasibility of using a stent-electrode array (Stentrode) to decode movements in sheep. In this study, two sheep were trained to perform an automated forced-choice task designed to elicit left and right head movement following an external stimulus. Cortical, movement-related signals were recorded using a Stentrode placed in the superior sagittal sinus adjacent to the motor cortex. Recorded brain signal was used to train a support vector machine classifier. Our results show that the Stentrode can be used to acquire motor-related brain signals to detect movement of the sheep in a forced-choice task. These results support the validity of using the Stentrode as a minimally invasive brain-machine interface.

Original language	English
Title of host publication	9th International IEEE EMBS Conference on Neural Engineering
Editors	Michel Maharbiz, Cynthia Chestek
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	750-753
Number of pages	4
ISBN (Electronic)	9781538679210
ISBN (Print)	9781538679227
DOIs	https://doi.org/10.1109/NER.2019.8717000
Publication status	Published - 2019
Event	International IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) Conference on Neural Engineering (NER) 2019 - San Francisco, United States of America Duration: 20 Mar 2019 → 23 Mar 2019 Conference number: 9th https://neuro.embs.org/2019/

Publication series

Name	International IEEE/EMBS Conference on Neural Engineering
Publisher	IEEE, Institute of Electrical and Electronics Engineers
ISSN (Print)	1948-3546
ISSN (Electronic)	1948-3554

Conference

Conference	International IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) Conference on Neural Engineering (NER) 2019
Abbreviated title	NER 2019
Country/Territory	United States of America
City	San Francisco
Period	20/03/19 → 23/03/19
Internet address	https://neuro.embs.org/2019/

Access to Document

10.1109/NER.2019.8717000

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Forsyth, I. A., Dunston, M., Lombardi, G., Rind, G. S., Ronayne, S., Wong, Y. T., May, C. N., Grayden, D. B., Oxley, T., Opie, N., & John, S. E. (2019). Evaluation of a minimally invasive endovascular neural interface for decoding motor activity. In M. Maharbiz, & C. Chestek (Eds.), 9th International IEEE EMBS Conference on Neural Engineering (pp. 750-753). (International IEEE/EMBS Conference on Neural Engineering). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/NER.2019.8717000

Forsyth, Ian A. ; Dunston, Megan ; Lombardi, Gabriel et al. / Evaluation of a minimally invasive endovascular neural interface for decoding motor activity. 9th International IEEE EMBS Conference on Neural Engineering. editor / Michel Maharbiz ; Cynthia Chestek. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2019. pp. 750-753 (International IEEE/EMBS Conference on Neural Engineering).

@inproceedings{17b2f4dbe29a45f5aa7587f9f5acb90f,

title = "Evaluation of a minimally invasive endovascular neural interface for decoding motor activity",

abstract = "Endovascular devices like the Stentrode{\texttrademark} provide a minimally invasive approach to brain-machine-interfaces that mitigates safety concerns while maintaining good signal quality. Our research aims to evaluate the feasibility of using a stent-electrode array (Stentrode) to decode movements in sheep. In this study, two sheep were trained to perform an automated forced-choice task designed to elicit left and right head movement following an external stimulus. Cortical, movement-related signals were recorded using a Stentrode placed in the superior sagittal sinus adjacent to the motor cortex. Recorded brain signal was used to train a support vector machine classifier. Our results show that the Stentrode can be used to acquire motor-related brain signals to detect movement of the sheep in a forced-choice task. These results support the validity of using the Stentrode as a minimally invasive brain-machine interface.",

author = "Forsyth, \{Ian A.\} and Megan Dunston and Gabriel Lombardi and Rind, \{Gil S.\} and Stephen Ronayne and Wong, \{Yan T.\} and May, \{Clive N.\} and Grayden, \{David B.\} and Thomas Oxley and Nicholas Opie and John, \{Sam E.\}",

year = "2019",

doi = "10.1109/NER.2019.8717000",

language = "English",

isbn = "9781538679227",

series = "International IEEE/EMBS Conference on Neural Engineering",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

pages = "750--753",

editor = "Michel Maharbiz and Cynthia Chestek",

booktitle = "9th International IEEE EMBS Conference on Neural Engineering",

address = "United States of America",

note = "International IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) Conference on Neural Engineering (NER) 2019, NER 2019 ; Conference date: 20-03-2019 Through 23-03-2019",

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}

Forsyth, IA, Dunston, M, Lombardi, G, Rind, GS, Ronayne, S, Wong, YT, May, CN, Grayden, DB, Oxley, T, Opie, N & John, SE 2019, Evaluation of a minimally invasive endovascular neural interface for decoding motor activity. in M Maharbiz & C Chestek (eds), 9th International IEEE EMBS Conference on Neural Engineering. International IEEE/EMBS Conference on Neural Engineering, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 750-753, International IEEE Engineering-in-Medicine-and-Biology-Society (EMBS) Conference on Neural Engineering (NER) 2019, San Francisco, California, United States of America, 20/03/19. https://doi.org/10.1109/NER.2019.8717000

Evaluation of a minimally invasive endovascular neural interface for decoding motor activity. / Forsyth, Ian A.; Dunston, Megan; Lombardi, Gabriel et al.
9th International IEEE EMBS Conference on Neural Engineering. ed. / Michel Maharbiz; Cynthia Chestek. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2019. p. 750-753 (International IEEE/EMBS Conference on Neural Engineering).

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

TY - GEN

T1 - Evaluation of a minimally invasive endovascular neural interface for decoding motor activity

AU - Forsyth, Ian A.

AU - Dunston, Megan

AU - Lombardi, Gabriel

AU - Rind, Gil S.

AU - Ronayne, Stephen

AU - Wong, Yan T.

AU - May, Clive N.

AU - Grayden, David B.

AU - Oxley, Thomas

AU - Opie, Nicholas

AU - John, Sam E.

N1 - Conference code: 9th

PY - 2019

Y1 - 2019

N2 - Endovascular devices like the Stentrode™ provide a minimally invasive approach to brain-machine-interfaces that mitigates safety concerns while maintaining good signal quality. Our research aims to evaluate the feasibility of using a stent-electrode array (Stentrode) to decode movements in sheep. In this study, two sheep were trained to perform an automated forced-choice task designed to elicit left and right head movement following an external stimulus. Cortical, movement-related signals were recorded using a Stentrode placed in the superior sagittal sinus adjacent to the motor cortex. Recorded brain signal was used to train a support vector machine classifier. Our results show that the Stentrode can be used to acquire motor-related brain signals to detect movement of the sheep in a forced-choice task. These results support the validity of using the Stentrode as a minimally invasive brain-machine interface.

AB - Endovascular devices like the Stentrode™ provide a minimally invasive approach to brain-machine-interfaces that mitigates safety concerns while maintaining good signal quality. Our research aims to evaluate the feasibility of using a stent-electrode array (Stentrode) to decode movements in sheep. In this study, two sheep were trained to perform an automated forced-choice task designed to elicit left and right head movement following an external stimulus. Cortical, movement-related signals were recorded using a Stentrode placed in the superior sagittal sinus adjacent to the motor cortex. Recorded brain signal was used to train a support vector machine classifier. Our results show that the Stentrode can be used to acquire motor-related brain signals to detect movement of the sheep in a forced-choice task. These results support the validity of using the Stentrode as a minimally invasive brain-machine interface.

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A2 - Maharbiz, Michel

A2 - Chestek, Cynthia

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Y2 - 20 March 2019 through 23 March 2019

ER -

Forsyth IA, Dunston M, Lombardi G, Rind GS, Ronayne S, Wong YT et al. Evaluation of a minimally invasive endovascular neural interface for decoding motor activity. In Maharbiz M, Chestek C, editors, 9th International IEEE EMBS Conference on Neural Engineering. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2019. p. 750-753. (International IEEE/EMBS Conference on Neural Engineering). doi: 10.1109/NER.2019.8717000

Evaluation of a minimally invasive endovascular neural interface for decoding motor activity

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