(IEEE 2019) The Method of Integrating Virtual Reality with Brainwave Sensor for an Interactive Math's Game

The implementation of the Virtual Reality (VR) on game is practical for in various fields, especially in the field of Education. The implementation of a mobile based VR game is example where the players of game feel as in the real world. However, the VR game has the weakness on limited interaction of their player with the virtual environment created by the game. Currently, the interactions pass through the buttons on mobile phone and joysticks. For this reason, this research investigates the alternative media to control the virtual environment of the game using brain sensor. The prototype was created using “mindwave neurosky” as brain sensor and thingkgear as sensor drive to construct the experiment of mobile based virtual reality math game. This research tests three modes signal including meditation, attention and beta signal. A meditation signal was taken when the player open and close the eye. While attention and beta signals were taken when the player focuses. The result is some model to control the VR math game with brain sensor for child five or six year old's

Wearable Human Computer Interface for control within immersive VAMR gaming environments using data glove and hand gestures

The continuous advances in the state-of-the-art in the Virtual, Augmented, and Mixed Reality (V AMR) technology are important in many application spaces, including gaming, entertainment, and media technologies. V AMR is part of the broader Human-Computer Interface (HCI) area focused on providing an unprecedentedly immersive way of interacting with computers. These new ways of interacting with computers can leverage the emerging user input devices. In this paper, we present a demonstrator system that shows how our wearable Virtual Reality (VR) Glove can be used with an off-the-shelf head-mounted VR device, the RealWear HMT-1™. We show how the smart data capture glove can be used as an effective input device to the HMT-1™ to control various devices, such as virtual controls, simply using hand gesture recognition algorithms. We describe our fully functional proof-of-concept prototype, along with the complete system architecture and its ability to scale by incorporating other devices