Vienna Liu
Pronouns: she/her
Research Mentor(s): David Lipps
Research Mentor School/College/Department: Movement Science / Kinesiology
Program: UROPF
Session: Session 2 (10:00am – 10:50am)
Authors: Vienna Liu, Amani Alkayyali, David Lipps
Abstract
A study was conducted to research more accurate and efficient methods to measure shoulder joint motion. A wearable shoulder patch was designed to calculate shoulder angles precisely. If proven to have equal or greater efficacy than its counterpart, the wearable shoulder patch will provide a more affordable and efficient means to measure shoulder angles. This measurement can be used in clinical settings, but aims to address research regarding breast cancer survivors. Specifically, this device has the potential to measure the motion of breast cancer patient’s arm movements after treatment. This movement is important to calculate because breast cancer surgeries like mastectomy can result in shoulder pain and reduced mobility. The methodology utilized in this project is currently in the testing phase to ensure that the hardware and software required to collect data works. The second step will be human subjects testing within the lab on individuals with and without shoulder pain. The findings are analyzed via data processing software, Nexus and Visual3D. Running the collected motion and angle data with a specific code, computes shoulder angles for the different positions. The main results have not been determined since the research has not formally begun. The main conclusion would involve whether shoulder angle data produced is the same from both the motion capture data and kirigami shoulder data. This research adds to the bigger picture as it aids in supporting breast cancer survivors. Furthermore, this device can ideally be utilized in other facets of sports research such as rehab for athletes with overuse injuries.
