Electromyogram (EMG) pattern recognition is essential for myoelectric hand control. This study describes a high precision motion discrimination system based on dummy variable features. The proposed method generates feature vectors with several dummy variables in order to improve the data distribution of six motions. Dummy variables are designed to improve the discrimination precision particularly for some motion pairs which are difficult to distinguish. Some experiments are performed to verify the effectiveness of the proposed motion discrimination method.