A Fuzzy Rule-Based Model of Vibrotactile Perception via an Automobile Haptic Screen

With the increased popularity of touch-sensitive surfaces, much attention has been drawn to their security-related issues, as they currently rely only on the visual sense for feedback. To improve operability, vibrotactile signals may be delivered to the finger on screen interaction. The way vibrotactile signals affect human perception is examined via three measured variables, related to their energy, velocity, and spectral complexity, and which are analytically defined in this paper. It is shown that these variables accurately account for the psychophysical properties of the tactile sense. Based on this, a psychophysical fuzzy rule-based model of vibrotactile perception is introduced to forecast the comfort values of the vibrational signals provided by an automobile haptic screen. Using an efficient rule-based generation method, a Mamdani fuzzy inference system is proposed; it achieves a mean error rate of 14% for the train set and 17% for the test set, while correctly classifying most of the signals within a reasonable tolerance, related to human evaluation imprecision. The system also produces a comprehensible linguistic rule structure, which allows behavioral patterns to be detected.