Accessible IoT

Towards Accessibility Assessment Toolkits for the Internet of Things

About

As the Internet of Things expands into all aspects of daily life, its potential to advance social good depends critically on accessibility for differently-abled users. This project develops Open Accessibility Assessment Toolkits for Inclusive IoT Design, enabling dynamic, in-situ system reconfiguration based on users' implicit feedback captured through on-body sensing technologies.

Research Vision: Dual-Approach Framework

Our research follows two complementary approaches that together create a comprehensive ecosystem for accessible IoT:

Approach 1: Helping Users

Detecting and Relieving Stress Through Physiological Sensing

We integrate sensors into everyday objects (umbrellas, earphones) to capture physiological signals unobtrusively, enabling real-time assessment of accessibility barriers and providing adaptive feedback for stress relief.

Key Systems: Affective Umbrella, MindSpace, OpenEarable ExG

Approach 2: Supporting Designers

Simulation Tools and Accessibility Awareness

We provide experiential learning tools that help designers understand the experiences of people with different abilities, embedding accessibility considerations from the earliest design stages.

Key Systems: Visual Impairment Simulation Glasses, Community Co-Design Studies

Explore our research outcomes →

Featured Prototypes

Affective Umbrella

Physiological sensing integrated into umbrella handle with real-time bio-feedback visualization. Validated through 21-person real-world study.

Seeing Our Blind Spots

Optical see-through smart glasses enabling dynamic visual impairment simulation. Published at UIST 2022.

MindSpace

Pneumatic haptic device simulating breathing for stress relief. 18-participant study showed improved relaxation and productivity.

OpenEarable ExG

Open-source ear-based biopotential sensing platform. MIT licensed, enabling eye-gaze interfaces and cognitive monitoring.

Learn more about our prototypes →

JST Presto Grant

Grant Number: JST Presto JPMJPR2132

Period: 2021-2025

Principal Investigator: Kai Kunze

This website showcases the research outputs and achievements from our JST Presto grant focusing on accessibility assessment tools for the Internet of Things.

Quick Stats

  • 30 Publications in top-tier venues (CHI, UIST, UbiComp, ETRA)
  • 29 Research Themes explored (2021-2025)
  • 4 Major Prototypes developed and validated
  • 2 Open-Source Platforms released (MIT licensed)
  • 40+ Citations demonstrating research impact
  • 6 International Workshops organized

View project timeline →

Contact

Email: kai@kmd.keio.ac.jp

Homepage: https://kaikunze.de

Institution

Graduate School of Media Design, Keio University