Overview of Study...

Monitoring of Daily Activities and Characterizing Related Contact Mechanics at the Knee in TKR Patients
Principal Investigator: Markus Wimmer, Ph.D.

Defining the Problem:

The performance of Total Knee Replacement (TKR) components is evaluated pre-clinically using mechanical knee joint simulation devices. Contemporary simulators use input data from gait analysis studies. However, this gait data is obtained from patients with healthy joints and does not accurately reflect the actual gait pattern and activity range of TKR patients. Gait data is available for TKR patients, but the daily activity profile including, sitting, walking, stair climbing, and other daily activities of an American TKR patient are yet undetermined. A functional patient activity monitoring device has been designed to record patient knee joint angles throughout a complete day. This data can be analyzed with custom written computer software in order to define a daily American TKR patient activity profile. Unsuccessful attempts have been made to incorporate the ability to gather kinetic data into the current monitoring device. Options for upgrading the existing activity monitor should be evaluated to identify a technique for gathering kinetic gait data over the course of a day, existing software should be upgraded to analyze this data, and activity profile information for American TKR patients should be collected using the new monitor and software.

Purpose:

The purpose of the project is to define a normal American TKR patient activity profile by monitoring patient activities. An activity monitor will be used to gather data, including a kinetic component if a design alternative that meets testing parameters is found. Existing data analysis software will be upgraded to more accurately and completely report the frequency and duration of patient activities.

Significance of the Study:

1. The kinematic data and activity profile data necessary to establish a standard American TKR patient activity simulation protocol will be collected for the first time.

2. Kinetic data could reveal forces experienced by the knee during daily activities.

3. The data analysis software will resolve the complete activity set into individual activities based on predetermined activity signatures.