If the Opensim GUI does not offer the option of a volume or strength-weighted cost function (I did not see it mentioned in the documentation), you will have to do it with the Opensim API. For each frame of data, the following steps would be needed: Ask Opensim to calculate the joint angles (inverse ...

You may want to try without residual reduction. Residual reduction is not required for static optimization, and could sometimes make things worse. I took a look at my own results with static optimization and the Delp 1990 musculoskeletal model [1]. Muscle activation results are provided as an Excel ...

Aaron, You could create a torque-driven model with force-length and force-velocity properties, which will help keep the torques realistic. It would look like: T = u * f1(angle) * f2(angular_velocity), where u is the control input. There would not be a series elasticity, or biarticular muscle effects...

That is an interesting observation and definitely possible for certain problems. With two objectives, this can be understood graphically. If you minimize J1 while keeping J2 constant (or the other way around), you get the Pareto front which is typically a monotonically decreasing function J2 = f(J1)...

I don't have access to the full paper so I only read the abstract. They mention "a force plate" which would be insufficient for RRA during double stance. It may be OK if the peak forces occurred during single stance and the double stance phase can be ignored. I would have used SO, and without RRA, t...

I would be interested in the reference to that work you mentioned. Maybe there is something I did not think about. In my understanding, RRA would only be valid in the single stance phase (not the whole stance phase) if you only have one force plate. This is because residual loads can't be reduced to...

The answer is yes, the knee joint forces will be correct, as long as you do not use the residual reduction algorithm (RRA). A suitable processing pipeline is: inverse kinematics, inverse dynamics, static optimization, joint reaction analysis. If you do the analysis this way, you don't need a full bo...

I did a lot of work with a 9-dof 2D model, and a standing initial was not even needed to generate walking. Solution success rate was close to 100% even with totally random numbers as initial guess. But I often get toe walking, a local optimum that is apparently easier to find. There are lower cost s...

Thanks, Ross! I also prefer to use standing as an initial guess for predictive walking simulations, so gait data are used which could bias the solution towards a particular (realistic) local minimum solution. Here is my approach and experience (outside of Moco, though). I just use one node and requi...

If you know that the velocity is always positive, that expression should work. The drag force will always be negative. But, the optimizer may sometimes evaluate a very weird trajectory, where a velocity is negative. If you get a negative drag force when the velocity is negative, your model will quic...