A methodology for multisensory product experience design using cross-modal effect: A case of SLR camera

TL;DR

This paper introduces a methodology for designing multisensory product experiences by leveraging cross-modal effects, demonstrated through a case study on SLR cameras to enhance sensory perception and user experience.

Contribution

It presents a novel approach combining Kansei modeling and regression analysis to systematically improve multisensory product design.

Findings

Validated methodology with SLR camera case study

Identified key cross-modal effects influencing perception

Provided solutions to enhance multisensory user experience

Abstract

Throughout the course of product experience, a user employs multiple senses, including vision, hearing, and touch. Previous cross-modal studies have shown that multiple senses interact with each other and change perceptions. In this paper, we propose a methodology for designing multisensory product experiences by applying cross-modal effect to simultaneous stimuli. In this methodology, we first obtain a model of the comprehensive cognitive structure of user's multisensory experience by applying Kansei modeling methodology and extract opportunities of cross-modal effect from the structure. Second, we conduct experiments on these cross-modal effects and formulate them by obtaining a regression curve through analysis. Finally, we find solutions to improve the product sensory experience from the regression model of the target cross-modal effects. We demonstrated the validity of the methodology with SLR cameras as a case study, which is a typical product with multisensory perceptions.