Mahalanobis Distances Based Brain Computer Interface for Hand Movement Imagery

• Main Authors: Chu, Tso-Yao, 朱作堯
• Other Authors: Lin, Chin-Teng
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/52639335813602490834

碩士 === 國立交通大學 === 影像與生醫光電研究所 === 99 === BCI is a communication pathway between the brain and external devices. It allows controlling external devices, such as robots, air conditioners, assistant technology devices, and other equipments, without muscles. Motor imagery-based BCI is one of systems working in asynchronous mode, and has been widely developed. However, many EEG channels are required to provide more efficient information related to movement imagery, and it also may cause the inconvenience in use.Under the consideration of using the least number of required EEG electrodes to recognize the event of hand-movement imagery, a Mahalanobis Distance (MD)-based BCI algorithm for movement imagery is proposed in this study. The models for right-hand and left-hand movement imageries can be derived by EEG power difference between the locations of C3 and C4. By using the MDs from different models of hand-movement imagery to provide more useful information, the accuracy of detecting hand- movement imagery can be effectively improved. The result shows the proposed MD-based BCI has been validated by hand-movement imagery experiment, and presents high performance of detecting hand-movement imagery under using the least number of required EEG electrodes.