2019 Graduate Student Showcase
 

Title of Submission

Developing an Angular Knee Jerk Algorithm Using Inertial Measurement Units

Degree Program

Kinesiology - Biophysical Studies, MS

Major Advisor Name

Tyler Brown

Type of Submission

Scholarly Poster

Abstract

Knee instability is reportedly a risk factor for osteoarthritis development. We hypothesize smoothness of knee motions, quantified as angular jerk, is indicative of joint instability. Up to 40 participants, will have jerk of frontal plane knee motion quantified while walking 3.0 mph for 60 minutes with three body borne loads (0, 15, and 30 kg). Custom MATLAB code will process inertial measurement units’ data to quantify peak and cost of angular knee jerk for frontal plane knee motions. Both peak and jerk cost of frontal plane knee motions are expected to be indicative of instability, increasing with load and fatigue.

This document is currently not available here.

Share

COinS