A Real Time Gesture Recognition with Wrist Mounted Accelerometer

This paper presents an acceleration based gesture recognition approach with wearable MEMS tri-axial accelerometer. In the application model, we have introduced frame based lookup table for gesture recognition. In accelerometer based gesture recognition concept, sensor data calibration plays an important aspect owing to their erroneous output due to zero-G error. In this work six-point based calibration of the sensor data is presented. The calibrated acceleration data so obtained from the sensor is represented in the form of frame-based signifier, to extract discriminative gesture information. It is observed that this procedure is always advantageous over conventional video image processing based gesture recognition that uses cameras and bulky computational algorithms. Thus, this accelerometer based gesture recognition not only reduces the hardware complexity but also minimizes the consumption of power by associated circuitry. Finally, this study helps us to develop a real time implementation of wearable gesture recognition device.