Due to their low cost and compact size, micro-electromechanical system-based inertial sensors have been utilized to detect human motion. This study presents a hand gesture recognition method with a three-axis accelerometer, gyroscope, and magnetometer attached to a wrist. First, sensor signals were applied to calculate the sensor’s orientation with a Kalman filter. These data were used to convert the sensor-frame acceleration signal to a global-frame acceleration signal (orientation calculation). Acceleration of motion was calculated by subtracting gravity from the global acceleration signal. The start and end of hand motion was detected by motion acceleration (motion segmentation). Segmented hand motion was recognized by gesture (gesture recognition). Six gestures (up, down, left, right, click, and double-click) were selected for implementation of the system, and the performance was evaluated.