• Login
  • Register

Work for a Member company and need a Member Portal account? Register here with your company email address.

Publication

Personalization, Expressivity, and Learnability of an Implicit Mapping Strategy for Physical Interfaces

David Merrill, Joseph A. Paradiso

Abstract

We present a new model for configuring the connections between user input and system output in a physical interface with diverse sensor degrees of freedom across several input modalities. Our system allows a user to demonstrate input gestures and manipulations directly to the system, teaching it the desired mappings by example. We developed a musical control application in which userdefined gestures and user-assigned manipulations trigger and modify sounds. The effectiveness of our system was tested by experimentally comparing our user-definable system to a similar, pre-configured version. The results suggest that users prefer to actively configure a physical interface to having expertly-configured presets. In addition, we propose our model as a more general mapping discovery tool for physical interface designers.

Related Content