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Rubbing a Physics Based Synthesis Model: From Mouse Control to Frictional Haptic Feedback

Authors: Onofrei, Marius George; Fontana, Federico; Serafin, Stefania;

Rubbing a Physics Based Synthesis Model: From Mouse Control to Frictional Haptic Feedback

Abstract

This paper investigates three kinds of interactions for a friction based virtual music instrument. The sound synthesis model consists of a bank of mass-spring-dampers excited via rubbing. A nonlinear static friction model capable of reproducing the characteristic stick-slip phenomenon observed in frictional interaction is employed, allowing for dynamic variation of the sliding friction. The different controls developed allow for gradually increasing the interplay between performer and instrument. The key excitation parameters, e.g., the rubbing velocity and the rubbing normal force are controlled using three different interfaces: a standard mouse, a Sensel Morph, and a 3D Systems Touch X. The Sensel Morph is a touchpad with pressure sensitivity, allowing for a natural exertion of the normal force; the 3D Systems Touch X is a haptic device that renders both resistance to the applied normal force, as well as the stick-slip motion resulting from the friction interaction. A preliminary user study aiming to compare the experience of performing with the different interfaces was carried out. The results indicate that the haptic feedback provides a more intuitive and enjoyable experience. However, extra features do not necessarily improve the user interaction, as the results suggest a preference for the mouse over the Sensel.

Countries
Italy, Denmark
Keywords

Physics-based model, real-time sound, multisensory feedback, haptics, friction

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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