Özet:
In this study, a mobile phone equipped with four
types of sensors namely, accelerometer, gyroscope, magnetometer
and orientation, is used for gesture classification. Without feature
selection, the raw data from the sensor outputs are processed and
fed into a Multi-Layer Perceptron classifier for recognition. The
user independent, single user dependent and multiple user
dependent cases are all examined. Accuracy values of 91.66% for
single user dependent case, 87.48% for multiple user dependent
case and 60% for the user independent case are obtained. In
addition, performance of each sensor is assessed separately and the
highest performance is achieved with the orientation sensor.