Device for Detection of Concussions Using Eye Tracking and Image Processing

Students: Katherine McCusker (CS), Caroline Shagnea (CS), Christopher Smith (CS), Mina Grace Larraquel (CS)
Advisor: Dr. Christopher Danek

The study of traumatic brain injuries has been growing in importance throughout the past decade.
Repeated concussions can cause severe deterioration of the brain, leading to permanent damage in
cognitive and emotional capabilities. Our goal is to combine artificial intelligence and eye tracking with
the most up to date findings in the neurological field to detect potential concussions in student athletes
at the time of injury. One of the earliest, and most common, signs of traumatic brain injury is
abnormality in eye movement. The athlete experiencing the concussion will likely have difficulty tracking
a moving object with their eyes. We have created a prototype device that uses a camera to track the eye
movements of someone with a potential concussion, and, based on a database of videos and photos,
calculate the probability of a concussion.

Wind Mapping Using Drone Technology

Students: Joey Lapointe (EE), Claire Sullivan (ME), Lauren Coene (ME), Brian Aberle (ME)
Advisor: Dr. Christopher Danek and Dr. Gregory Behrmann

Our project concept was to build an ultrasonic anemometer mounted onto a tethered drone, with hopes
of making wind energy a realistic solution for people in rural areas. A drone was donated to our team
that met all payload requirements. It can fly for 25 minutes on its own, and over three hours when
connected to a tether. We built an ultrasonic anemometer to measure wind speed and direction. We
tested it by using a wind tunnel to expose the anemometer to different measured wind speeds and
comparing each to the anemometer’s wind speed calculation. Using our design build test cycle we will
be able to design and construct an ultrasonic anemometer that can accurately measure wind speed and
direction. The entirety of our testing plan requires further development, but we will proceed with
confidence in both the capabilities of our equipment and the need for our product.

Power-Assisted Device for Manual Wheelchairs

Students: Jeffery Guile (CS), Peter Larson (BME), Kristine Nguyen (CS)
Advisor: Dr. Christopher Danek and Dr. Gregory Behrmann

Wheelchair users face many daily challenges, such as obstacles on sidewalks, or steep slopes. After
talking to many wheelchair users at the National Rehab Hospital in Washington, D.C., we found that one
of their most pertinent decisions is choosing between their manual or power wheelchairs while traveling
independently. Our design allows users to add a power boost to their manual wheelchair. The design
consists of adjustable components to accompany the various dimensions of wheelchairs, so it will fit all
manual wheelchairs. Users with different types of mobility disabilities will be able to control the device
by using a joystick or using a push button interface. Our team created a power assist device for manual
wheelchair users that is easy for users to apply, detach, and carry, and reliable. By using human-
centered design, we were able to create a prototype by combining our vision with constant customer
and stakeholder feedback.

Smart Specs Obstacle Detection for the Visually Impaired

Students: Husam Alkifigee (EE), Bada Alsolimani (EE), Mohammed Binkhurayyif (EE), Maria Galle (ME)
Advisor: Dr. Christopher Danek and Dr. Gregory Behrmann

Research done in 2019 indicates that there are more than 39 million blind people who live with
challenges such as walking and navigating through day to day activities; there is a clear need for a
solution. Our purpose is to help blind people by providing a solution that uses object recognition to
identify objects that may obstruct their path while walking such as a person, cup, branch, bottle, or stop
sign. The device enables blind people to gain enough confidence to carry out their daily activities. We
will accomplish the mission by outlining a comprehensive analysis of the device which uses sensors and
cameras that will help blind people. Introduction of the device would increase the mobility of blind
people living with visual impairments.

Breakaway Device for an Osseointegrated Prosthetic

Students: Christopher Cupo (ME), Mariangelica Bermudez Gonzalez (ME), Ashley Sieber (ME), Ann Vogel (ME)
Advisor: Dr. Christopher Danek and Dr. Gregory Behrmann

This design challenge is to benefit a wounded veteran who lost his leg in combat and required a device
that would allow him to be more active so he can do what he loves, mountain biking. Due to
complications with his amputation and a traditional socket prosthetic, the subject and his medical team
opted for an osseointegration implant system. This system implants a titanium rod in our challenger’s
femur in a two-step process. This allows for a direct connect between the prosthetic and the rod. The
breakaway device developed will detach into two pieces due to axial loads in both tension and
compression, torsion, and bending. The breakaway device detaches his prosthetic from the implant
system when impact exceeds a threshold, preventing injury. This device will improve our challenger’s
quality of life and allow him to resume his passion for mountain biking.

Autonomous Boat to Scan Surrounding Water for Hurricane Relief

Students: George Isaacs (EE), Tien Pham (CS), Kevin Jay (ME), Alex Braziel (CS), Luke Nicholson (ME)
Advisor: Dr. Christopher Danek, Dr. Gregory Behrmann, and Jon Haase

After hurricane Dorian in the summer of 2019, we were tasked with trying to solve the “last mile”
package delivery problem for our senior design project. We were eager to tackle this problem, but we
also wanted to do something meaningful in the process. We saw the tragedies occurring after the
hurricane as an opportunity for us to help victims not only get their critical supplies, but also help the
supply runners deliver the supplies quicker. We determined the best way to streamline the delivery
process was to autotomize the sonar scanning of the surrounding water. Much of the hurricane debris is
thrown into the water, prohibiting ships carrying supplies and personnel from coming ashore. We
decided to solve this issue by hacking into a Fish Finder to receive GPS and sonar data. Using this data,
we created a path algorithm to navigate the waters in the most efficient manner.

Foldable Housing for Displaced People

Students: Mansour Aburamyah (CE), Saad Alhai (CE), Saud Alenezi (CE)
Advisor: Dr. Christopher Danek and Dr. Gregory Behrmann

We aim to improve the lives of people who are displaced from their homeland. We developed a design
concept for foldable housing that meets the needs of refugees living in camps. This housing system
provides security, privacy, and protection from adverse weather. Our foldable housing system is easy to
move by flatbed truck and can be assembled by only a few people. Housing systems can be configured
for multiple purposes and constructed from materials that allow long term use (3 to 5 years).