THE SCHOOL OF INDUSTRIAL DESIGN 

GEORGIA INSTITUTE OF TECHNOLOGY 

Under the provisions of the regulations for the degree 

MASTER OF INDUSTRIAL DESIGN 

on

Wednesday, April 8, 2026

9:30 a.m. – 10:30 a.m. EST 

West Architecture 250

Teams Link:  Thesis Defense: Modular Rehabilitation Robotics: A Platform for Personalized and Data-Driven Therapy_Ruijie Jin | Meeting-Join | Microsoft Teams

Ruijie Jin

will present a thesis defense entitled, 

"Modular Rehabilitation Robotics: A Platform for Personalized and Data-Driven Therapy"

  Advisor: 

Dr. Leila Aflatoony, Georgia Tech School of Industrial Design 

Committee:  

Dr. Eunsook Kwon, Georgia Tech School of Industrial Design 

Dr. Yixiao Wang, Georgia Tech School of Industrial Design 

Faculty and students are invited to attend this presentation. 

Abstract  

Access to effective rehabilitation is limited by high costs, workforce shortages, and insufficient therapy intensity, while existing robotic systems remain inaccessible due to their expense and complexity. This thesis presents an open-source modular rehabilitation robotics platform that integrates robotic joint modules, a guided parametric interface, and customizable 3D-printed components to support personalized therapy.

Semi-structured interviews with ten rehabilitation experts informed the development of key design guidelines, followed by an iterative human-centered design process and iterative prototyping of the system to refine both the software interface and physical hardware. An initial usability evaluation with ten non-expert participants showed that users could independently complete measurement and modeling tasks, indicating the feasibility of accessible customization workflows.

A final evaluation with thirteen participants further demonstrated the system’s broader impact, highlighting its potential to enhance therapist–patient communication through shared data and visualization, reduce economic barriers associated with rehabilitation devices, and increase the feasibility of home-based rehabilitation.

These findings suggest that modular, parametric, and open-source approaches can extend access to rehabilitation technology beyond clinical settings. This work contributes a design framework for accessible and scalable rehabilitation systems, supporting more sustainable and user-driven therapy.