Integrated 2D Motion Analysis System

Overview

Anterior Cruciate Ligament (ACL) tears are a common injury among athletes who exert a significant amount of force and torque on their knee. A pre-existing system has been developed to analyze an athlete’s movements as he or she is recorded while jumping on a force sensor. The analyzed data ultimately outputs an athlete’s risk of tearing his or her ACL. This system presents challenges regarding a manual and independent data collection with components that do not interface with each other. This project aimed to improve the functionality of the pre-existing system by automating the data collection process, the data synchronization, and the results that are displayed.

Objectives

The objective of this project is to develop an automated system that is portable, easy to use, reliable, has a specified functionality, and maintains a high-quality video. The overall objective, of course, is to be able to collect data to properly analyze an athlete’s risk of tearing his or her ACL.

Approach

• Met with Sponsor to learn about the customer needs and asked questions to learn as many details as possible about the current system.
• Conducted thorough research on pre-existing methods, various hardware options, and potential coding techniques.
• Developed an objective tree to assist in creating Engineering Requirements.
• Developed a multi-level system design.
• Consulted with MATLAB forums to learn more about coding techniques specific to MATLAB.
• Performed testing throughout the entire project as well as on the system as a whole once implementation was complete.
• Validated results through multiple calculations and compared motion data to force data using videos, timestamps, and plots.
• Generated results which include the following:
  • Video of the athlete jumping.
  • Plots of the athlete’s landing force with respect to (w.r.t.) time, moment w.r.t. time, and horizontal and vertical positions w.r.t. time.
  • Message displaying the athlete’s risk of tearing his or her ACL based on a certain threshold.

Outcomes

This project resulted in an improved system that significantly reduces the current set up and analysis time. Additionally, this system is easy to use due the user-friendly human machine interface, the automatic data collection, synchronization, and result generation.