Sensitivity and specificity of upper extremity movements decoded from electrocorticogram

An H. Do; Po T. Wang; Christine E. King; Andrew Schombs; Jack J. Lin; Mona Sazgar; Frank P K Hsu; Susan J. Shaw; David E. Millett; Charles Y. Liu; Agnieszka A. Szymanska; Luis A. Chui; Zoran Nenadic

doi:10.1109/EMBC.2013.6610824

Sensitivity and specificity of upper extremity movements decoded from electrocorticogram

An H. Do, Po T. Wang, Christine E. King, Andrew Schombs, Jack J. Lin, Mona Sazgar, Frank P K Hsu, Susan J. Shaw, David E. Millett, Charles Y. Liu, Agnieszka A. Szymanska, Luis A. Chui, Zoran Nenadic

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

7 Scopus citations

Abstract

Electrocorticogram (ECoG)-based brain computer interfaces (BCI) can potentially be used for control of arm prostheses. Restoring independent function to BCI users with such a system will likely require control of many degrees-of-freedom (DOF). However, our ability to decode many-DOF arm movements from ECoG signals has not been thoroughly tested. To this end, we conducted a comprehensive study of the ECoG signals underlying 6 elementary upper extremity movements. Two subjects undergoing ECoG electrode grid implantation for epilepsy surgery evaluation participated in the study. For each task, their data were analyzed to design a decoding model to classify ECoG as idling or movement. The decoding models were found to be highly sensitive in detecting movement, but not specific in distinguishing between different movement types. Since sensitivity and specificity must be traded-off, these results imply that conventional ECoG grids may not provide sufficient resolution for decoding many-DOF upper extremity movements.

Original language	English (US)
Title of host publication	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages	5618-5621
Number of pages	4
DOIs	https://doi.org/10.1109/EMBC.2013.6610824
State	Published - 2013
Externally published	Yes
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

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

Computer Vision and Pattern Recognition
Signal Processing
Biomedical Engineering
Health Informatics

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10.1109/EMBC.2013.6610824

Cite this

Do, A. H., Wang, P. T., King, C. E., Schombs, A., Lin, J. J., Sazgar, M., Hsu, F. P. K., Shaw, S. J., Millett, D. E., Liu, C. Y., Szymanska, A. A., Chui, L. A., & Nenadic, Z. (2013). Sensitivity and specificity of upper extremity movements decoded from electrocorticogram. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 5618-5621). Article 6610824 https://doi.org/10.1109/EMBC.2013.6610824

Sensitivity and specificity of upper extremity movements decoded from electrocorticogram. / Do, An H.; Wang, Po T.; King, Christine E. et al.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 2013. p. 5618-5621 6610824.

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

Do, AH, Wang, PT, King, CE, Schombs, A, Lin, JJ, Sazgar, M, Hsu, FPK, Shaw, SJ, Millett, DE, Liu, CY, Szymanska, AA, Chui, LA & Nenadic, Z 2013, Sensitivity and specificity of upper extremity movements decoded from electrocorticogram. in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS., 6610824, pp. 5618-5621, 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.2013.6610824

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abstract = "Electrocorticogram (ECoG)-based brain computer interfaces (BCI) can potentially be used for control of arm prostheses. Restoring independent function to BCI users with such a system will likely require control of many degrees-of-freedom (DOF). However, our ability to decode many-DOF arm movements from ECoG signals has not been thoroughly tested. To this end, we conducted a comprehensive study of the ECoG signals underlying 6 elementary upper extremity movements. Two subjects undergoing ECoG electrode grid implantation for epilepsy surgery evaluation participated in the study. For each task, their data were analyzed to design a decoding model to classify ECoG as idling or movement. The decoding models were found to be highly sensitive in detecting movement, but not specific in distinguishing between different movement types. Since sensitivity and specificity must be traded-off, these results imply that conventional ECoG grids may not provide sufficient resolution for decoding many-DOF upper extremity movements.",

author = "Do, {An H.} and Wang, {Po T.} and King, {Christine E.} and Andrew Schombs and Lin, {Jack J.} and Mona Sazgar and Hsu, {Frank P K} and Shaw, {Susan J.} and Millett, {David E.} and Liu, {Charles Y.} and Szymanska, {Agnieszka A.} and Chui, {Luis A.} and Zoran Nenadic",

year = "2013",

doi = "10.1109/EMBC.2013.6610824",

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AU - Sazgar, Mona

AU - Hsu, Frank P K

AU - Shaw, Susan J.

AU - Millett, David E.

AU - Liu, Charles Y.

AU - Szymanska, Agnieszka A.

AU - Chui, Luis A.

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AB - Electrocorticogram (ECoG)-based brain computer interfaces (BCI) can potentially be used for control of arm prostheses. Restoring independent function to BCI users with such a system will likely require control of many degrees-of-freedom (DOF). However, our ability to decode many-DOF arm movements from ECoG signals has not been thoroughly tested. To this end, we conducted a comprehensive study of the ECoG signals underlying 6 elementary upper extremity movements. Two subjects undergoing ECoG electrode grid implantation for epilepsy surgery evaluation participated in the study. For each task, their data were analyzed to design a decoding model to classify ECoG as idling or movement. The decoding models were found to be highly sensitive in detecting movement, but not specific in distinguishing between different movement types. Since sensitivity and specificity must be traded-off, these results imply that conventional ECoG grids may not provide sufficient resolution for decoding many-DOF upper extremity movements.

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ER -

Sensitivity and specificity of upper extremity movements decoded from electrocorticogram

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