Categorisation of Mobile EEG: A Researcher's Perspective - PubMed
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Categorisation of Mobile EEG: A Researcher's Perspective
Anthony D Bateson et al. Biomed Res Int. 2017.
Abstract
Researchers are increasingly attempting to undertake electroencephalography (EEG) recordings in novel environments and contexts outside of the traditional static laboratory setting. The term "mobile EEG," although commonly used to describe many of these undertakings, is ambiguous, since it attempts to encompass a wide range of EEG device mobility, participant mobility, and system specifications used across investigations. To provide quantitative parameters for "mobile EEG," we developed a Categorisation of Mobile EEG (CoME) scheme based upon scoring of device mobility (D, from 0, off-body, to 5, head-mounted with no additional equipment), participant mobility (P, from 0, static, to 5, unconstrained running), system specification (S, from 4, lowest, to 20, highest), and number of channels (C) used. The CoME scheme was applied to twenty-nine published mobile EEG studies. Device mobility scores ranged from 0D to 4D, participant mobility scores from 0P to 4P, and system specification scores from 6S to 17S. The format of the scores for the four parameters is given, for example, as (2D, 4P, 17S, 32C) and readily enables comparisons across studies. Our CoME scheme enables researchers to quantify the degree of device mobility, participant mobility, and system specification used in their "mobile EEG" investigations in a standardised way.
Figures
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Various mounting positions of the EEG device and associated equipment on the participant. (a) All equipment is off-body mounted and participant tethered via cabling to EEG acquisition equipment. (b) Waist-mounted (or back-mounted) with additional equipment located in a rucksack. (c) All equipment is waist-mounted. (d) Head-mounted EEG system, with additional equipment located (i) in a rucksack or (ii) off-body tethering participant via limited-range wireless link. (e) Head-mounted and requires smartphone/tablet. (f) Head-mounted. Acquisition, storage, and analysis equipment is integrated within the headset.
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3D plot showing the device and participant mobility scores and the system specification scores for each selected research investigation and associated EEG systems. Refer to Table 8 for the number of channels used in each selected study.
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References
-
- Castermans T., Duvinage M., Petieau M., et al. Optimizing the performances of a P300-based brain-computer interface in ambulatory conditions. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 2011;1(4):566–577. doi: 10.1109/JETCAS.2011.2179421. - DOI
-
- Lotte F., Fujisawa J., Touyama H., Ito R., Hirose M., Lécuyer A. Towards ambulatory brain-computer interfaces: A pilot study with P300 signals. Proceedings of the International Conference on Advances in Computer Entertainment Technology, ACE 2009; October 2009; Athens, Greece. pp. 336–339. - DOI
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