Pca and eigenvalue interpretation

[martinbandung]

hello, i have a reasearch to analyse the movement of human walking using pca. i did it like this
1. i dibide the body into some part (thigh, foot, hand, etc)
2. i film it so i can track the x position of the parts
3. i get the x to t graph for every part
4. i make a matrix which column is the position x for every parts, and rows is the position for each time
5. i gind the pca of the matrixquestion
how do i interpret the data?
what is the meaning of the eigen values?
what correlation berween first principle component and second principle component?

what further analysis can i get from doing pca?

thanks for the answers

 

[chiro]

Hey martinbandung.

I think you should outline the PCA technique you are using.

If you are modeling joints and "nodes" of a body then you use something called kinematics. Forward kinematics is when you adjust each node for a new position based on how all "nodes" move and inverse kinematics is when you solve for the "node" positions given final positions for some of the "nodes" (and then solve for the remaining ones).

The technique is covered in a lot of computer animation and physics books.

Principal Component Analysis (PCA) is a statistical technique and is separate from kinematics which is a physics topic.