AnyBody

Hi to gorup,

I am new comer to the group. It may irritate you but really i am not
able to understand how AnyBody works in case of Muscle recruitment.

  1. DOF are constrainded by dirvers and some by joints and when I
    loaded the standing model execpt them i all so see some a word
    ‘‘others’’, what does it mean by Others!

  2. I knew the equations of motion are less than unknowns. I mean how
    you tackle the problem of Indeterminancy?

  3. Simply I know we have three equations of equilibrimum and three
    unknowns and when unknowns are more than no. of equations then we have
    indeterminate system.

In AnyBody model standing model how many unknows we have and how
we solve them because we have just three equations.

How does works the optimization of muscle recruitment?

I hope to get answers of question and get solved my problems.

Regards.

JH

Hi JH?

Welcome to the group

Here are some answers to the questions:

1: The “others” include the kinematics constraints which do not fall into
the group of joint and drivers, so typically this is tailor made joints. So
if you for example define a AnyKinEq this will go into the “other” folder.

2: The indeterminancy is handled by an optimization algorithm, there are
several papers which explains about this, below I have selected some of the
papers from http://anybody.aau.dk/publications.htm

Rasmussen, J., Damsgaard, M. & Voigt, M. (2001): Muscle recruitment by the
min/max criterion - a comparative numerical study. Journal of Biomechanics,
vol. 34, no. 3, pp. 409-415.

M. Damsgaard, J. Rasmussen & S.T. Christensen (2001): Inverse dynamics of
musculo-skeletal systems using an efficient min/max muscle recruitment
model. Proceedings of IDETC: 18-th Biennial Conference on Mechanical
Vibration and Noise, Pittsburgh, September 9-13, 2001.

Michael Damsgaard, John Rasmussen, Søren Tørholm Christensen, Egidijus
Surma, and Mark de Zee (2006): Analysis of musculoskeletal systems in the
AnyBody Modeling System. Simulation Modelling Practice and Theory. Volume
14, Issue 8 , November 2006, Pages 1100-1111. Elsevier, ISSN: 1569-190X.

3: In 3D we each body has 6 dof, three position and three rotations. If you
apply more than six reactions to this body it will be indeterminate.

In the standing model we have more than three dof. We have 330 rigid body
dof, this is because we have 54 segments so 54x6=330.

The kinematic constraints adds up to 330 too, so the problem is
kinematically determinate, we drive exactly the correct amount of dof.

This is the constraint listing of the problem.

Total number of constraints:

Joints: 167

Drivers: 129

Other: 34

Total: 330

In terms of reaction forces in the model we have 260 so this leaves 70
reactions free to be carried by the approximately 500 muscles, the
distribution of the forces between the muscles are handled by the muscle
recruitment algorithm.

I hope this made things clearer, otherwise please write again.

Best regards

Søren, AnyBody Support


From: anyscript@yahoogroups.com [mailto:anyscript@yahoogroups.com] On Behalf
Of johni555
Sent: 09 June 2008 15:46
To: anyscript@yahoogroups.com
Subject: [AnyScript] AnyBody

Hi to gorup,

I am new comer to the group. It may irritate you but really i am not
able to understand how AnyBody works in case of Muscle recruitment.

  1. DOF are constrainded by dirvers and some by joints and when I
    loaded the standing model execpt them i all so see some a word
    ‘‘others’’, what does it mean by Others!

  2. I knew the equations of motion are less than unknowns. I mean how
    you tackle the problem of Indeterminancy?

  3. Simply I know we have three equations of equilibrimum and three
    unknowns and when unknowns are more than no. of equations then we have
    indeterminate system.

In AnyBody model standing model how many unknows we have and how
we solve them because we have just three equations.

How does works the optimization of muscle recruitment?

I hope to get answers of question and get solved my problems.

Regards.

JH

[Non-text portions of this message have been removed]