Abstract

This capstone will explore the affordability (and therefore accessibility) of soft robotics for assistive technologies – with the goal of developing technology that can be brought out of the lab and into real-world environments throughout the city, such as in people’s homes or in communal robotic gyms. This is part of a larger effort to democratize healthcare for the well-being of all citizens. This capstone is not about building robots – it’s about using data and literature to assess the viability of affordable solutions for novel soft robotic technologies.

Project Description & Overview

This project will compare the cost of soft vs non-soft rehabilitation solutions.

We will start by breaking the problem down into different rehabilitation tasks, and we will look at what types of robotic devices could be used to perform those tasks. Either devices out on the market or still in research. For those out on the market, we will look at the cost of those devices, and what components go into creating that cost.

We can narrow the problem down by focusing on upper-arm solutions (whereas lower-body solutions can be an entirely different ballgame.) These devices include rigid exoskeletons and soft exosuits. One can consider the haptic gloves, for example, that are out on the market.

Separately, we will look at robots used in other domains (ie manufacturing) and look at the costs of those devices.

We will also survey the different soft robotic systems that are out on the market in different applications, and assess the cost of those devices. We will consider the different materials that are used to make the soft components, and whether this changes the cost.

We will brainstorm on different ways that soft robotics can be used in urban healthcare settings.

We will survey the literature on the affordability of soft robotics, and specifically the affordability of soft robotics in healthcare and rehabilitation. We can use these literature reviews as a starting point for our work.

Datasets

There are no datasets provided for this project. Students will be expected to use their data science background to identify relevant datasets that can help with the project. This could include datasets related to:

• Cost of rehabilitative healthcare
• How the pandemic prevented hospital care
• How citizens use community centers and public gyms, and how this varies across socio-economic demographics
• The relationship between amount of care and health improvement for various types of rehabilitation

Competencies

• Data science and informatics
• Economics/financial analysis
• Experience or courses in entrepreneurship, operations, research, business, design and manufacturing
• Industrial engineering
• User experience design
• Mechanical engineering background
• Electrical/controls systems engineering background

Learning Outcomes & Deliverables

1. A publication-ready report. If possible, we can publish a survey paper on the affordability of soft robotics for rehabilitation.
2. An interactive website that turns the information in the survey report into smaller modules that users can explore and read about. This can also include graphics and links.

Students

Sreya Chakraborty, Xinnuo Li, and Amy Zheng