A Fundamental Study on Control of CG Character using Brain Wave Discrimination
- 10.2991/jrnal.k.211108.013How to use a DOI?
- Brain–machine interface (BMI); computer graphics (CG); electroencephalography (EEG); the fast Fourier transform (FFT); support vector machine (SVM); virtual reality (VR)
Virtual Reality (VR) has grown with the development of computer Graphics (CG). In recent years, VR technology is expected to develop in various fields such as medical, welfare, education, training, tourism, business, entertainment, and so on. This paper aims at intuitive operation by focusing on troublesome mounting in VR. When using VR equipment, it is required to set up many cables and sensors. In addition, when using it, there must always have a certain space around the user, because we always use the controller when operating in the world of VR, for reasons of care or for the safety of the user. Therefore, the location must be selected when the VR device is used. Furthermore, we also verified whether the VR space can be operated just by thinking in the head of a device that is economic than the device used in the existing study. As a method to solve this issue, we propose manipulation method of CG character by Electroencephalography (EEG). We use the brain–machine interface to measure brain waves, the fast Fourier transform and the support vector machine as the methods of EEG analysis in this paper. In the future, we will continue our study using different approaches of EEG analysis and new conditions by changing the method of EEG analysis and other conditions.
- © 2021 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
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TY - JOUR AU - Makoto Sakamoto AU - Kenji Sakoma AU - Taketo Kamasaka AU - Kodai Miyamoto AU - Amane Takei AU - Tsutomu Ito AU - Takao Ito PY - 2021 DA - 2021/12/27 TI - A Fundamental Study on Control of CG Character using Brain Wave Discrimination JO - Journal of Robotics, Networking and Artificial Life SP - 293 EP - 297 VL - 8 IS - 4 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.k.211108.013 DO - 10.2991/jrnal.k.211108.013 ID - Sakamoto2021 ER -