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Sensor-based gesture interaction technology has been widely adopted inconsumer electronics. Nevertheless, bias, drift, and noise existing in sensorsignals are difficult to eliminate, and accurate movement trajectoryinformation is still needed to achieve flexible interaction application. Thispaper presents micro-electro-mechanical system (MEMS) motion sensorinformation processing algorithms designed on a gesture interaction systemwhich integrates multiple low-cost MEMS motion sensors with ZigBee wirelesstechnology to support embodied communication while acting together withmachines. Sensor signal processing systems mainly solve noise removal, signalsmoothing, gravity influence separation, coordinate system conversion, andposition information retrieval. The attitude information which is animportant movement parameter and required by position estimation iscalculated with a quaternion-based extended Kalman filter (EKF). Theeffectiveness of the movement information retrieval of this gesture interfaceis verified by experiments and test analysis, both in static and movingcases. In the end, related applications of the described sensor informationprocessing are discussed

Advanced information processing of MEMS motion sensors for gesture interaction