Bioengineering Senior Design

• Design a force sensing apparatus to measure tongue protrusion strength in rodents

  PROJECT PARTNER // Department of Otolaryngology and Communicative Disorders, University of Louisville

  PROJECT DESCRIPTION

  We designed and produced a device that measures the maximum tongue protrusion force that will be used to study rats undergoing treatment for head and neck cancer. This was accomplished by building a modified licking device, which consists of a horizontal plate attached to a force transducer and a mini liquid pump that allows water to be pushed from a reservoir out onto the plate. The rat will need to protrude their tongue pushing against the plate at a certain force to receive a liquid reward. When the plate is pressed down at the target force the sensor is triggered allowing our program to collect force/temporal measures and release water onto the plate.

  BENEFITS TO PROJECT CLIENT

  Swallowing dysfunction is a common problem after treatment for head and neck cancer. Movement of the tongue is critical for feeding and there is evidence that cancer treatment can compromise tongue strength during swallowing. This device will allow our client to characterize oral sensorimotor impairments attributed to cancer and its treatment, as well as test pharmaceutical therapies aimed at improving tongue function.

  PROJECT GOAL

  The goal of this project is to develop a force-sensing apparatus that records and analyzes maximum tongue protrusion forces and temporal measures during drinking in the rat.

  TEAM MEMBERS

  • Keats Ripy
  • Caleb Vaughn
  • Jenna Wilkerson

• A machine-learning software that predicts outcomes of COVID-19 patients

  PROJECT DESCRIPTION
  

  The final product is a software bundle with two machine-learning algorithms: (1) an algorithm that predicts whether a patient will need to be intubated for a prolonged period of time, defined as 4, 14, or 21+ days; and (2) an algorithm that predicts whether a patient on certain cardiac medications will experience a severe outcome, defined as expiration, cardiac arrest and myocardial infarction (MI). The project was to create the underlying algorithms by coding in the programming language R using machine-learning models. Statistical analysis was also performed on the data to unveil statistically significant relations between predictors and outcomes.

  BENEFITS TO PROJECT CLIENT

  The software will be beneficial, as it will serve as a tool for clinicians to determine accurate prognoses for their COVID-19 patients. As a result, patients will receive quicker and better treatment that can reduce the probability of mortality and other severe outcomes. Additionally, with an increased number of efficient and effective treatments, hospitals will save money on supplies, and clinicians will have more time for other patients and tasks.

  PROJECT GOAL

  The primary long-term goal is to provide a prognosis tool for clinicians to use when they are formulating treatment plans for their patients. With a targeted AUROC, a measure of accuracy, of .90, the machine learning algorithm will be able to provide excellent differentiation between groups of COVID-19 patients with designated predictor values.

  TEAM MEMBERS

  • Mary Baxter
  • Katya Kovatsenko

• Mechanotype-based Sorting Device for Improved Cancer Diagnosis

  PROJECT DESCRIPTION
  

  The project intends to use the preestablished link between cancer cell stiffness and cancer cell aggression for cancer diagnosis by creating a device capable of separating cancer cells based on stiffness. The current design is a microfluidic chip which utilizes fluid dynamics and the mechanical properties of a cell to separate cells into groups based on stiffness. The number of cells in each group can then be calculated and used to evaluate cancer aggression.

  BENEFITS TO PROJECT CLIENT

  1. Provides a relatively quick means for cancer aggression evaluation.
  2. Supplies a cheaper alternative to other diagnosis methods.
  3. Creates a means for additional cancer diagnosis verification.

  PROJECT GOAL

  The main goal of the project is to create a microfluidic device capable of sorting cells based on stiffness for the evaluation of cancer cell aggression.

  TEAM MEMBERS

  • Lauren Garrett
  • Nathan Scott

• TAG Pediatric Wheelchair Motorized Attachment

  PROJECT DESCRIPTION
  

  Manual wheelchairs are difficult to operate across certain terrains and grades for the pediatric population. This adds extra strain to their underdeveloped shoulders or can cause a lack of independence if assistance is required from a parent or caregiver. Current motorized wheelchair attachment products are too heavy, powerful, and expensive for many patients in the pediatric population to use effectively. Due to these many disparities, a new motorized attachment for manual pediatric wheelchairs is warranted.

  BENEFITS TO PROJECT CLIENT

  1. The attachment will be better suited for pediatric users in comparison to other market competitors as it will be lightweight
  2. The attachment will provide braking when the user is going downhill
  3. The attachment will provide power assistance to help users maneuver uphill and over certain terrains.

  PROJECT GOAL

  The goal of this project is to create a motorized wheelchair attachment prototype for pediatric patients that will fit onto a manual pediatric wheelchair and provide sufficient and controlled power to operate across certain terrains.

  TEAM MEMBERS

  • Amelia Franxman
  • Gabrielle Ogle
  • Tanner Weilage