This paper, presents an evaluation of Three Dimensional (3D) unistroke human arm gestures. Our scheme employs an accelerometer-based approach by using Nintendo� Wiimote as a gesture device. The system takes acceleration signals from Wiimote in order to, classify different gestures. It deals with numeric gestures, i.e., digits from 0 to 9 and simple mathematical operator gestures for addition, subtraction, multiplication and division. Two techniques, Dynamic Time Warping (DTW) and 2D trajectories are used to recognize and classify gestures. Successful recognition rates indicate that performing 3D gestures using accelerometer-based devices is intuitive and provides an effective means of interaction with computers. © 2015, Zarka Private Univ. All rights reserved.