A Preliminary Study on Precision Image Guidance for Electrode Placement in an EEG Study
- 294 Downloads
Conventional methods for positioning electroencephalography electrodes according to the international 10/20 system are based on the manual identification of the principal 10/20 landmarks via visual inspection and palpation, inducing intersession variations in their determined locations due to structural ambiguity or poor visibility. To address the variation issue, we propose an image guidance system for precision electrode placement. Following the electrode placement according to the 10/20 system, affixed electrodes are laser-scanned together with the facial surface. For subsequent procedures, the laser scan is conducted likewise after positioning the electrodes in an arbitrary manner, and following the measurement of fiducial electrode locations, frame matching is performed to determine a transformation from the coordinate frame of the position tracker to that of the laser-scanned image. Finally, by registering the intra-procedural scan of the facial surface to the reference scan, the current tracking data of the electrodes can be visualized relative to the reference goal positions without manually measuring the four principal landmarks for each trial. The experimental results confirmed that use of the electrode navigation system significantly improved the electrode placement precision compared to the conventional 10/20 system (p < 0.005). The proposed system showed the possibility of precise image-guided electrode placement as an alternative to the conventional manual 10/20 system.
KeywordsElectroencephalography (EEG) EEG electrode placement International 10/20 system Landmark identification Registration Navigation
This work was supported by the DGIST R&D Program of the Ministry of Science, ICT and Future Planning (17-BD-0401). Part of this study was reported at the Asian Conference on Computer Aided Surgery held in Singapore in 2015, at the International IEEE EMBS Conference on Neural Engineering held in Montpellier France in 2015 and at the 30th International Congress of Computer Assisted Radiology and Surgery held in Heidelberg Germany in 2016, respectively. The authors thank Hyunseok Choi, a PhD candidate from DGIST, for his valuable help on software programming.
This study was funded by the DGIST R&D Program of the Ministry of Science, ICT and Future Planning (17-BD-0401).
Compliance with Ethical Standards
Conflict of interest
The authors declare that they have no conflict of interest.
For this type of study, formal approval is not required.
Informed consent was obtained from all individual participants included in the study.
- Besl PJ, McKay ND (1992) Method for registration of 3-D shapes. In: Robotics-DL tentative. pp 586–606Google Scholar
- Bradski G, Kaehler A (2008) Learning OpenCV: Computer vision with the OpenCV library. O’Reilly Media, Inc., FarnhamGoogle Scholar
- Chatrian GE, Lettich E, Nelson PL (1985) Ten percent electrode system for topographic studies of spontaneous and evoked EEG activities. Am J EEG Technol 25:83–92Google Scholar
- Figueiredo CP, Dias NS, Hoffmann K-P, Mendes PM (2008) 3D electrode localization on wireless sensor networks for wearable BCI. In: Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE. pp 2365–2368Google Scholar
- Klem GH, Luders HO, Jasper HH et al (1999) The ten-twenty electrode system of the International Federation. Electroencephalogr Clin Neurophysiol 52:3–6Google Scholar
- Koessler L, Cecchin T, Ternisien E, Maillard L (2010) 3D handheld laser scanner based approach for automatic identification and localization of EEG sensors. In: Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. pp 3707–3710Google Scholar
- Munoz-Salinas R (2012) ARUCO: a minimal library for Augmented Reality applications based on OpenCvGoogle Scholar
- Sanderson C et al (2010) Armadillo: an open source C + + linear algebra library for fast prototyping and computationally intensive experimentsGoogle Scholar
- Wilm J (2010) Iterative Closest Point. https://www.mathworks.com/matlabcentral/fileexchange/27804-iterative-closest-point. Accessed 27 Jun 2017