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1.
Appl Ergon ; 58: 128-136, 2017 Jan.
Article in English | MEDLINE | ID: mdl-27633205

ABSTRACT

Although EEG experiments over the past decades have shown numerous applications for brain-computer interfacing (BCI), there is a need for user-friendly BCI devices that can be used in real-world situations. 3D anthropometry and statistical shape modeling have been shown to improve the fit of devices such as helmets and respirators, and thus they might also be suitable to design BCI headgear that better fits the size and shape variation of the human head. In this paper, a new design method for BCI devices is proposed and evaluated. A one-size-fits-all BCI headset frame is designed on the basis of three digital mannequins derived from a shape model of the human head. To verify the design, the geometric fit, stability and repeatability of the prototype were compared to an EEG cap and a commercial BCI headset in a preliminary experiment. Most design specifications were met, and all the results were found to be similar to those of the commercial headset. Therefore, the suggested design method is a feasible alternative to traditional anthropometric design for BCI headsets and similar headgear.


Subject(s)
Brain-Computer Interfaces , Cephalometry/methods , Electroencephalography/instrumentation , Equipment Design/methods , Head/anatomy & histology , Adult , Electrodes , Ergonomics , Female , Humans , Male , Young Adult
2.
Appl Ergon ; 48: 70-85, 2015 May.
Article in English | MEDLINE | ID: mdl-25683533

ABSTRACT

This paper presents the evaluation a 3D shape model of the human head. A statistical shape model of the head is created from a set of 100 MRI scans. The ability of the shape model to predict new head shapes is evaluated by considering the prediction error distributions. The effect of using intuitive anthropometric measurements as parameters is examined and the sensitivity to measurement errors is determined. Using all anthropometric measurements, the average prediction error is 1.60 ± 0.36 mm, which shows the feasibility of the new parameters. The most sensitive measurement is the ear height, the least sensitive is the arc length. Finally, two applications of the anthropometric shape model are considered: the study of the male and female population and the design of a brain-computer interface headset. The results show that an anthropometric shape model can be a valuable tool for both research and design.


Subject(s)
Models, Anatomic , Scalp/anatomy & histology , Adult , Anthropometry , Brain-Computer Interfaces , Computer-Aided Design , Female , Head/anatomy & histology , Humans , Magnetic Resonance Imaging , Male , Young Adult
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