結合虛擬實境中老鷹於直線賽道遊戲建立腦機介面之注意力訓練場景

Combining with an Eagle of Virtual Reality on Straight Track Game to Establish an Attention Training Scene of Brain Computer Interface

本研究主要為神經方面受損的患者透過腦機介面（Brain Computer Interface, BCI）量測患者的腦波特徵並利用虛擬實境（Virtual Reality, VR）製作遊戲動畫來建立患者在復健運用更有趣的注意力訓練遊戲復健虛擬場景，提供患者復健量化指標。本研究之遊戲場景結合了Unity遊戲軟體、Arduino Leonardo藍芽模板和NeuroSky公司的單通道腦波儀（MindWave Mobile 1）來讀取腦電波（Electroencephalogram, EEG）訊號特徵，藉由BCI使大腦與遊戲中角色直接溝通進行訓練。受測者為作者本人，演算法歸類專注與放鬆來控制遊戲角色老鷹的飛行軌跡計算訓練的正確率。本研究實際測試結果分為三天進行測試，每天平均做十五次的實際測試，而得三天樣本的平均正確率分別為67.53%、70.07%、71.93%。利用t-test計算且p>0.05，結論得出本研究成功地建立了穩定的虛擬實境之注意力遊戲訓練場景系統，測試方便且實用之系統，未來也希望達到本研究之目的，應用於腦神經之臨床專注力訓練復健相關研究。

This study mainly aims to measure the brain wave features of the patients and use virtual reality (VR) by brain computer interface (BCI) to create game animations building an interesting rehabilitation scenes of attention training games for patients with neurological damage and supporting a rehabilitation quantization index of patients. This study’s game scene combined Unity game software, Arduino Leonardo bluetooth module and NeuroSky’s single channel brain wave instrument (MindWave Mobile 1) to read the features of electroencephalogram (EEG) signals to conduct the training by BCI with characteristic of the game. The subject was the author himself. The algorithm generalized attention and relaxation to control the character’s flying track of the game calculating the training accuracy. The test results of this study were divided into three-day tests. An average of 15 actual tests were performed every day. The average accuracy rates of the three days were67.53%, 70.07%, and 71.93% respectively. Using t-test calculation for these three days obtained the value p>0.05. It was concluded that the stable virtual reality game system of attention game training is successfully established. It was a convenient and practical system. In the future, it is hoped that the system will be applied to the research on clinical concentration training and rehabilitation of cranial nerves.