Medical Devices for Ophthalmology and Assistive Devices for Visually Impaired

Medical Devices for Ophthalmology and Assistive Devices for Visually Impaired

VisionOverview

This VIP team is working on several design projects in collaboration with University of Michigan Department of Ophthalmology and Visual Sciences, located at the Kellogg Eye Center. The projects include surgical devices, diagnostic tools, and assistive devices for people with low vision. More project ideas are introduced regularly, each with the overall goal goals of helping ophthalmologists treat/diagnose their patients and assisting people with low vision in living a better and safer life.

First year through graduate students are welcome to apply, and all will be encouraged to stay on the team for more than the two-semester minimum. Leadership roles are available in the lab, and experienced students will be a natural fit for these positions as their knowledge grows over time.

 The team currently has the following ongoing projects:

Vision Assistive Device

This project is to develop a product that for people with low vision that can make activities of daily life, such as grocery shopping and operating appliances, much easier to perform. The user will be offered enhanced depth perception, as well as magnified images.

Smart Anti-Slip Cane

Many visually-impaired people rely on the use of a cane to navigate. The cane allows early detection of obstacles and can even provide some feedback about the roughness of the floor a user is about to step onto. However, it is not possible for a user to discern between slippery and smooth surfaces, knowledge which could lead to a reduction in falls. This project focuses on the creation of a device that can be attached to a regular cane that helps to detect slippery floor conditions.

Haptic Interface for 3D Object Reconstruction

This project aims to create a tool that can help the visually impaired understand and explore 3D shapes. This project will develop a device that can reproduce 3D shape of any computer generated models.

More Information: 2017-Assisted-Vision

Students who successfully match to this faculty research team will be required to sign the following document in January 2017:

Student IP Agreement for Faculty Research Teams

How to Apply

Project Features

  • Skill level All levels
  • Students 5-11
  • Likely Majors Any, BME, CS, ECE, EE, MSE, ME
  • Course Substitutions ECE Cognate
  • IP & NDA Required? Yes
  • Summer Opportunity Summer Funding Application
  • Hardware Design (2 Students)

    Specific Tasks: mechatronics/mechanical design, CAD modeling, basic machining, 3D printing

    • Likely Majors: ME, ANY
  • Electrical Design (4 Students)

    Specific Tasks: circuit design, PCB layout, wireless communication, instrumentation, image processing, general programming

    • Likely Majors: EE, ECE, CSE/CS-LSA
  • Human Interfacing (2 Students)

    Specific Tasks: materials selection, ensuring bio-compatibility, incorporation of human factors into design

    • Likely Majors: BME, MSE
  • Apprentice Researcher (3 Students)

    Requirements: interest in project material, willingness to develop skills. OPEN TO FRESHMEN AND SOPHOMORES ONLY.

    • Likely Majors: ANY

Faculty Sponsor: Lauro Ojeda Justin Kasper
Assistant Research Scientist

Lauro Ojeda has over 18 years of experience in the fields of: inertial sensing, sensor data fusion, estimation techniques, Kalman filtering, biomechanics and human gait analysis. Ojeda started his career in the field of robot localization systems combining dead-reckoning and inertial sensing, and he later moved to the field of human positioning estimation. Ojeda was the first to propose a practical approach for inertial-based personal localization, which is currently used widely across the world. His work in this field was later adapted to medical applications, specifically unrestrictive gait analysis. His work on this field is currently being used in several labs at the University as well as other research centers and commercial companies. Ojeda has over 40 papers and four patents in the field of position estimation and inertial sensing.