Application of Synchronized Backscatter Sensors to Sign Language Motion Classification

In the classification of sign language motion, it is vital to measure the movements of many points on human body. While the method of calculating the nodal coordinates of human body from camera image is limited to the detection of two dimensions, acceleration sensor can detect three-dimensional movements. In this investigation, on the measurement of sign language motion, we used a backscatter communication system, which enables synchronized multi-channel reception of sensor signals from battery-free sensors. Acceleration sensors were attached to four locations on both wrists and elbows, and data were acquired from four signers. SVM was used as the classifier, and the classification accuracy was evaluated for 20 sign language words by cross-validation. The experiment demonstrated that classification accuracy of 86.0% to 91.0% could be obtained using this setup.