Validating the Location and Tracking of a Human’s Center of Mass Using a Statically Equivalent Serial Chain
This project seeks to validate the use of a statically equivalent serial chain (SESC) in locating and tracking a human’s center of mass (CoM). The statically equivalent serial chain used in this project is comprised of 13 parameters, each roughly corresponding to a portion of the human body. Given these 13 parameters, the SESC points directly at a person’s CoM. Every individual has a unique set parameters to calculate their SESC. These parameters are determined by capturing poses and using the body segment length and position information, as well as the center of pressure reading, acquired from the different poses. A Wii Balance Board and Xbox Kinect were used in this study as inexpensive force plate and motion capture systems. There are other methods for calculating a person’s center of mass, but these require expensive equipment and more complex computational processes. The method proposed here is a low cost, fast, and easy way to accurately predict a person’s CoM. In order to determine the feasibility of the SESC model, subjects of varying body types were tested, and SESC predictions for the CoM were checked for both accuracy and repeatability. A minimum number of poses required to achieve an accurate CoM prediction was determined by figuring out where subject’ parameters converged, which increases time efficiency of the process. Additionally, it was found that the number of frames required to capture a pose could be decreased from 30 to 15 frames without sacrificing accuracy. This resulted in a total testing and setup time of 30 minutes per subject, opposed to one hour previously. Thus, validating the SESC method as a fast, easy, and fairly accurate solution for predicting a human’s CoM.
Andrew P Murray, David A Perkins
Primary Advisor's Department
Mechanical and Aerospace Engineering
Stander Symposium poster
"Validating the Location and Tracking of a Human’s Center of Mass Using a Statically Equivalent Serial Chain" (2018). Stander Symposium Posters. 1311.