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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

Towards Online Functional Brain Mapping and Monitoring During Awake Craniotomy Surgery Using ECoG-Based Brain-Surgeon Interface (BSI)

verfasst von : L. Yao, T. Xie, Z. Wu, X. Sheng, D. Zhang, N. Jiang, C. Lin, F. Negro, L. Chen, N. Mrachacz-Kersting, X. Zhu, D. Farina

Erschienen in: Brain-Computer Interface Research

Verlag: Springer International Publishing

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Abstract

During brain surgery, functional brain mapping is critical, and the time needed for the procedure should be reduced to the minimum in order to avoid risks for the patient. In this project, we extend the traditional concept of BCI for communication and control between brain and external devices, to the concept of Brain-Surgeon Interface (BSI) in order to establish an interactive channel between the patient’s brain and the surgeon, with the ultimate goal of a high quality and precise brain surgery. Compared with “intraoperative fMRI”, which is expensive and time-consuming, or cortical electrical stimulation, which may cause epilepsy and brain swelling during the surgery, the proposed ECoG-based BSI system works in an online scenario, and the mapping time can be significantly reduced to a half minute for both motor and sensory cortex. Three signal modalities were used for functional brain mapping: movement related cortical potential, steady-state somatosensory evoked potential, event-related (de)synchronization. The proposed BSI system may provide a considerable advantage for clinical brain surgery applications.

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Vorheriges Kapitel Predicting Motor Intentions with Closed-Loop Brain-Computer Interfaces
Nächstes Kapitel A Sixteen-Command and 40 Hz Carrier Frequency Code-Modulated Visual Evoked Potential BCI
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Metadaten
Titel
Towards Online Functional Brain Mapping and Monitoring During Awake Craniotomy Surgery Using ECoG-Based Brain-Surgeon Interface (BSI)
verfasst von
L. Yao
T. Xie
Z. Wu
X. Sheng
D. Zhang
N. Jiang
C. Lin
F. Negro
L. Chen
N. Mrachacz-Kersting
X. Zhu
D. Farina
Copyright-Jahr
2017
Buch
Brain-Computer Interface Research

Print ISBN: 978-3-319-64372-4

Electronic ISBN: 978-3-319-64373-1

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-64373-1_9

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