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Application of magnetic field sensors for hand gesture recognition with neural networks

Hand motion tracking represents one of the most widely used human-computer interface. Those technologies are essential for virtual reality (VR) systems recognition of human movements or the interpretation of gestures. For such tasks numerous systems are utilized, which often combine magnetic field and inertial measurement systems. This is done to enable a six degree of freedom (DOF)position. Often time extensive modeling effort is necessary. In the following a sensing methodology is presented, which distinguishes itself via the exclusive application of magnetic field sensing. The recorded positions of this measurements are the input of a neural network that is trained to recognize the gesture of the hand depending on the position of the fingers.