Selection and Design of Keyboard Switches Based on the Human Feeling

Abstract

People sometimes recognize a system which is of a high grade by both the feel and/or sound of it's keyboard switches when pushed. A keyboard whose switches when pressed, have a feeling that is neither too nor too light, and which also convey a clear confirmation of switching makes a computer. We focus on the man-machine interface of the keyboard and investigate the human feelings of touch and push as the engineering matter in question in order to design switches comfortable to operate. First, the categories (words) that can quantitatively characterize the switch pushing feeling were selected. Next, the sensory tests by questionnaire using these categories were carried out to acquire sensory data that relate both the feeling and the switch's physical characteristic. Finally, the artificial neural networks to store the sensory data were trained. The pattern of the touching feeling degrees expressed by the categories is used as the input data for training the patterns given by physical characteristics of switches are used as the output data. The trained artificial neural networks have the potential to select the most preferable switch and provides the physical quantities necessary to design, just by grading each item in the switch selection sheet very similar to that used in the questionnaire.