Abstract
Recently, information terminals such as mobile phone are widely used. However, these devices are not always comfortable and convenient to use because of their small shape. Consequently, we need to develop a new type of the input interface whose operation is easier and shape is smaller. Electromyogram (EMG) is generated along to the person's behavior and it has information, which contains of the level of behavior. Especially, learning and recognition of EMG by using neural networks, is supposed to be possible. We have shown its basic ability and possibility by the simulation for the realization of the practical use on the wrist behavior recognition. Furthermore, we consider about online tuning of neural network for robust of fluctuation of individual wrist behavior
