Quantitative assessment of friction perception for fingertip touching with different roughness surface

AbstractThere are many mechanical stimulation receptors and sensory nerve endings in human skin, which are the important tools in tactile perception. It is a complex process for human to perceive objects and friction relative motion plays an important role during this process. When human’s fingertips friction against objects, they will produce compression and tensile mechanical deformation, which can stimulate the mechanical stimulation receptors in fingertip skin to produce corresponding action potentials and impulses signals. The signals which contain object’s physical properties are transmitted to cerebral cortex by nervous system, thus the shape and surface texture of objects are perceived. Thus the friction between the fingertip and object is an important factor to perceive objects. There exist positive connection between friction and tactile perception. However, limited quantitative parameters can be used to evaluate the perception, and they have rarely been studied scientifically. In this paper, the friction perceptions of fingertip skin rubbing against different roughness sandpapers were studied by biofeedback of frictional signals, physiological and psychological responses. An UMT-II tribometer was used to measure tribological parameters of the fingertip, and corresponding physiological response of electroencephalogram (EEG) signals were monitored by using a Physiological Monitoring and Feedback Instrument (NeXus-10) with BioTrace+software. The psychological responses were scored according to the volunteer’s perception during friction tests. The correlation models among the perception of fingertip, friction coefficient and EEG signals were established by applying regression analysis method. Results showed that the friction coefficient, amplitudes of EEG signals and psychological responses increased with the roughness of sandpapers increasing. There existed a significant correlation among the friction perception of different surface roughness, friction coefficient and amplitudes of EEG signals. By using this method, the perception of fingertip skin for different roughness surface during friction can be evaluated quantitatively