A Modular Haptic Display with Reconfigurable Signals for Personalized Information Transfer

TL;DR

This paper introduces a customizable, modular soft haptic display system that uses an information-theoretic approach to personalize feedback, enabling rapid hardware reconfiguration and optimized information transfer for individual users.

Contribution

The work presents a novel modular hardware platform combined with an information-theoretic algorithm for personalized, reconfigurable haptic feedback in human-machine interfaces.

Findings

Modular hardware enables rapid reconfiguration of haptic signals.

Personalization improves effectiveness of haptic communication.

User studies confirm the benefits of modularity and customization.

Abstract

We present a customizable soft haptic system that integrates modular hardware with an information-theoretic algorithm to personalize feedback for different users and tasks. Our platform features modular, multi-degree-of-freedom pneumatic displays, where different signal types, such as pressure, frequency, and contact area, can be activated or combined using fluidic logic circuits. These circuits simplify control by reducing reliance on specialized electronics and enabling coordinated actuation of multiple haptic elements through a compact set of inputs. Our approach allows rapid reconfiguration of haptic signal rendering through hardware-level logic switching without rewriting code. Personalization of the haptic interface is achieved through the combination of modular hardware and software-driven signal selection. To determine which display configurations will be most effective, we model haptic communication as a signal transmission problem, where an agent must convey latent information to the user. We formulate the optimization problem to identify the haptic hardware setup that maximizes the information transfer between the intended message and the user's interpretation, accounting for individual differences in sensitivity, preferences, and perceptual salience. We evaluate this framework through user studies where participants interact with reconfigurable displays under different signal combinations. Our findings support the role of modularity and personalization in creating multimodal haptic interfaces and advance the development of reconfigurable systems that adapt with users in dynamic human-machine interaction contexts.